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Monday, June 24
 

08:30

Welcome & Registration
Monday June 24, 2019 08:30 - 09:00

09:00

Building a Simple Recommender System From Scratch — Training Workshop
This training workshop will take place before the main conference. It will be given in a small classroom, to maximize interaction and so you can ask even more questions than in a conference setting.

IMPORTANT:
  • A specific ticket is required to get access to the workshop ("Workshop WORKSHOP_NAME + Conference 24-26/6").
  • The venue is different from that of the main conference. The workshop will be held at Dafiti — many thanks to them for providing the space!
  • Students should bring their own laptops, for practical work. 
----

SUMMARY
We will implement and deploy a whole recommender system from scratch, going from simple techniques to more advanced ones. Numpy and Scipy will be used at first, to understand the basic principles; then, a TensorFlow adaptation will be implemented and deployed to production. For this, we will be querying data simulated from Dafiti (which amounts to a few gigabytes), preparing it for the algorithm, training the model serverlessly, and finally building the frontend architecture for the serving step. Google Cloud AI Platform will be used through the whole process (the code and steps that we will present can be used with other public cloud providers, or in private clouds).

TARGET AUDIENCE
Machine learning practitioners interested in learning more about recommender systems and how to fully deploy them into production, going from a real source of data input to recommendations offered to the customers.

LEARNING OBJECTIVES
  • Basic and advanced Collaborative Filtering algorithms
  • Data processing
  • Deployment of a serverless system following best practices
  • Implement a serverless frontend infrastructure to serve recommendations

PROGRAM
Recommendation algorithms:
  • Exploring concepts of collaborative filtering with implicit feedback in Python
  • Going from naive implementations to more sophisticated ones using Numpy / Scipy
  • Adapting the code to TensorFlow (so we can later deploy in a serverless environment)
  • Unit testing

Data preparation:
  • Querying data simulated from Dafiti (~10 GB)
  • Analyzing the data, cleaning it, and preparing it for usage in the recommendation algorithm

Deployment:
  • Preparing the TensorFlow model previously implemented for training on Google Cloud AI Platform
  • Executing a training / test strategy for validating performance

Frontend serving:
  • After our model has been deployed, we then proceed on building a simple Python web service that will handle input requests for recommendations, process the whole thing and send back the processed response
  • A final examination will be made to analyze recommendations performance

GET YOUR WORKSHOP TICKET NOW!

Speakers
avatar for Willian Fuks

Willian Fuks

Data Scientist, Dafiti Group
Working as a Data Scientist at Dafiti Group mainly focused in recommender systems, optimization techniques, A/B testing and search engines. Holds a Master Degree in Artificial Intelligence by Escola Politécnica da USP.


Monday June 24, 2019 09:00 - 17:00
Dafiti Group — Room LYON Av. Francisco Matarazzo, 1350 - Água Branca, São Paulo - SP, 05001-100, Brazil

09:00

Deep Learning Kickstart with Keras — Training Workshop
This training workshop will take place before the main conference. It will be given in a small classroom, to maximize interaction and so you can ask even more questions than in a conference setting.

IMPORTANT:
  • A specific ticket is required to get access to the workshop ("Workshop WORKSHOP_NAME + Conference 24-26/6").
  • The venue is different from that of the main conference. The workshop will be held at Dafiti — many thanks to them for providing the space!
  • Students should bring their own laptops, for practical work. They will be given access to GPU-equipped machines in the cloud, for hands-on experiments with deep learning.
----

SUMMARY
Deep Learning is one of the most exciting research areas in artificial intelligence. It has achieved outstanding results in Computer Vision and Natural Language Processing. In this hands-on workshop for beginners, we will teach you about the basic concepts of Deep Learning and present some popular models: Deep Feedforward Neural Networks (DFNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). Our focus is on applying these models to real life problems. Hence we will show how to formulate those problems in a way that can be solved by Deep Learning methods.


LEARNING OBJECTIVES
  • Understand how to build basic Deep Learning models for image and text.
  • Practical guidance on how to structure and train your model.
  • Learn Keras for a faster transition from idea to product.


PROGRAM
Introduction
  • Machine learning review
  • Neural network basics
  • Keras: basic usage
  • Hands-on: Lane following as regression (self-driving car task)

Convolutional Neural Networks (CNN)
  • Convolution in image processing
  • Transfer Learning
  • Hands-on: Lane following as image classification with CNN

Recurrent Neural Networks (RNN)
  • Text as training data
  • Word Embeddings
  • Understating RNN and its extensions: LSTM and GRU
  • Hands-on: Sentiment analysis

Conclusions
  • Recap
  • Advanced topics:
  • Transferability analysis (transfer learning tips)
  • What's new in NLP? BERT
  • Useful resources


 STUDENT REQUIREMENTS
  • All the Hands-on exercises will be coded in Python. Therefore, we expect basic knowledge of that language. If you want to review basic Python concepts, you can refer to https://www.codecademy.com/learn/learn-python 
  • Bring your own laptop for hands-on practical work.

Speakers
avatar for Paula Moraes

Paula Moraes

MSc Candidate, IME-USP
avatar for Felipe Salvatore

Felipe Salvatore

PhD Candidate, USP
Felipe Salvatore is a Ph.D. candidate at the University of São Paulo where he focuses on the natural language problem of dialog generation using Machine Learning. After graduating from a Master's in Logic, he became interested in Artificial Intelligence and started collaborating... Read More →


Monday June 24, 2019 09:00 - 17:00
Dafiti Group — Room MARSEILLES Av. Francisco Matarazzo, 1350 - Água Branca, São Paulo - SP, 05001-100, Brazil

09:00

Machine Learning for Managers — Training Workshop
This training workshop will take place before the main conference. It will be given in a small classroom, to maximize interaction and so you can ask even more questions than in a conference setting.

IMPORTANT:
  • A specific ticket is required to get access to the workshop ("Workshop WORKSHOP_NAME + Conference 24-26/6").
  • The venue is different from that of the main conference. The workshop will be held at Dafiti — many thanks to them for providing the space!
  • Students are invited to bring their own laptops, if they want to replicate the hands-on demo (optional — see program below). 
----

SUMMARY

Managers have a key role to play to make Machine Learning (ML) work for any organization. This non-technical but practical workshop is the first to be designed for operational and technical managers with no prior knowledge of ML. It provides the missing piece to identify the best opportunities with Machine and Deep Learning (DL) technologies, to apply them in your own projects, and to generate business value from data.

This workshop is focused not on teaching algorithms, but on how to make them work in the real world, and on key knowledge to start managing ML projects effectively. It will bring you up to speed on core ML concepts, illustrated with example use cases, and it will demystify ML/DL with a hands-on demo of a point-and-click and automated tool to compete in a Data Science challenge. You will learn how to set up and structure a successful ML project, and how to set direction for your team's work, with the help of the Machine Learning Canvas. You will apply your learnings in a team exercice, where you will collaborate with others to create an MLC.

If you are a Manager, you will save months of work for your whole team by understanding the principles taught in this workshop. If you are a Developer or a Scientist, this is the workshop to recommend to your Manager, to better understand what today’s ML techniques can/cannot do, and how.

BONUS — Free ebooks for all participants: Bootstrapping Machine Learning and The Machine Learning Canvas


TARGET AUDIENCE
Operational managers, technical managers and technical decision-makers


LEARNING OBJECTIVES
  • Understand the unique opportunities ML creates, and its limitations. 
  • Design domain-specific evaluation procedures and performance metrics.
  • Learn how to use the ML Canvas to frame ML problems, design real-world ML systems, and set up your own ML projects.

PROGRAM
Possibilities and limitations of ML
  • Core concepts of supervised learning: classification and regression
  • Categorization of use cases and business applications; examples
  • Preparing data for ML: from data collection to feature engineering
  • Why/when ML fails

Hands-on demo: competing in a Kaggle challenge without coding
  • Creating the best model for your data with “auto ML” techniques on BigML
  • Making predictions with the model
  • Submitting to Kaggle

Evaluating ML systems
  • Using problem knowledge to design test datasets properly
  • Designing domain-specific performance metrics

Formalizing ML problems
  • Bridging the gap between predictions, decisions, and value
  • Specifying ML systems with the Machine Learning Canvas
  • Application of the Canvas to example ML use cases (team exercice)

Conclusions
  • Recap of key takeaways
  • Where to go from here

GET YOUR WORKSHOP TICKET NOW!

Speakers
avatar for Louis Dorard

Louis Dorard

General Chair, PAPIs
Louis Dorard is the author of Bootstrapping Machine Learning, of the Machine Learning Canvas, General Chair of PAPIs.io (international conferences on ML applications and APIs), and Adjunct Teaching Fellow at UCL School of Management.As an independent consultant and Machine Learning... Read More →



Monday June 24, 2019 09:00 - 17:00
Dafiti Group — Room PARIS Av. Francisco Matarazzo, 1350 - Água Branca, São Paulo - SP, 05001-100, Brazil

09:00

Machine Learning on AWS with SageMaker — Training Workshop
This training workshop will take place before the main conference. It will be given in a small classroom, to maximize interaction and so you can ask even more questions than in a conference setting.

IMPORTANT:
  • A specific ticket is required to get access to the workshop ("Workshop WORKSHOP_NAME + Conference 24-26/6").
  • The venue is different from that of the main conference. The workshop will be held at Dafiti — many thanks to them for providing the space!
  • Students should bring their own laptops, for practical work. 
----

SUMMARY
In this workshop, we will use Amazon SageMaker to build, train and deploy Machine Learning models. Running a number of Jupyter notebooks, you will first learn how to use built-in algorithms to perform complex tasks like image classification or classification. Then, we'll see how you can bring your own Tensorflow or Apache MXNet script to train Deep Learning models. We’ll also cover advanced topics like hyper parameter optimization, cost optimization and more.

WHAT YOU WILL LEARN
  • What Amazon SageMaker is
  • How to build end-to-end Machine Learning workflows on Amazon SageMaker
  • How to use built-in ML algorithms for classification, image recognition, etc.
  • How to bring your own model, your own training code, etc.
 
PRE-REQUISITES
  • AWS account
  • Familiarity with core AWS services (IAM, S3, EC2, etc.)
  • Familiarity with Python
  • Basic understanding of Machine Learning concepts

GET YOUR WORKSHOP TICKET NOW!

Speakers
avatar for Julien Simon

Julien Simon

AI Evangelist, AWS
As the Artificial Intelligence & Machine Learning Evangelist for EMEA, Julien focuses on helping developers and enterprises bring their ideas to life. He's also actively blogging at https://medium.com/@julsimon. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering... Read More →


Monday June 24, 2019 09:00 - 17:00
Dafiti Group — Room VERSAILLES Av. Francisco Matarazzo, 1350 - Água Branca, São Paulo - SP, 05001-100, Brazil
 
Tuesday, June 25
 

08:15

Welcome & Registration
Doors open at 8.15am. We strongly recommend to arrive early in order to have time to go through security, get your PAPIs badge, choose your favorite t-shirt (we have some really cool and exclusive designs, but limited sizes), meet fellow attendees, exhibitors, and find a good seat in the auditorium. We’ll also have breakfast snacks, fruit, tea, coffee and refreshments!

Tuesday June 25, 2019 08:15 - 09:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

09:00

Opening remarks
Speakers
avatar for Dan Nichol

Dan Nichol

Program Chair, AnalyticsFC
I build football data analytics tools for better recruitment at professional teams. Previously, I worked a postdoc studying the evolution of drug resistance in cancer.
avatar for Ana Paula Appel

Ana Paula Appel

Researcher and Data Scientist, IBM Research
Ana Paula is a Research Staff Member in IBM Research - Brazil, currently work with large amount of data to do Science WITH Data and Science OF Data at IBM Research Brazil. My technical interesting are in data mining and machine learning area specially in graph mining techniques for... Read More →
avatar for Louis Dorard

Louis Dorard

General Chair, PAPIs
Louis Dorard is the author of Bootstrapping Machine Learning, of the Machine Learning Canvas, General Chair of PAPIs.io (international conferences on ML applications and APIs), and Adjunct Teaching Fellow at UCL School of Management.As an independent consultant and Machine Learning... Read More →


Tuesday June 25, 2019 09:00 - 09:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

09:30

Reinforcement Learning for devs: toolkits, and application to autonomous race cars
Reinforcement Learning is a Machine Learning technique particularly suitable for complex, unpredictable, environments that can be simulated and where building a prior dataset would either be infeasible or prohibitively expensive. In this session, we'll introduce the main concepts of RL and pre-packaged RL toolkits available in Amazon SageMaker. We'll also talk about AWS Deep Racer, a fully autonomous 1/18th scale race car driven by RL.

Speakers
avatar for Julien Simon

Julien Simon

AI Evangelist, AWS
As the Artificial Intelligence & Machine Learning Evangelist for EMEA, Julien focuses on helping developers and enterprises bring their ideas to life. He's also actively blogging at https://medium.com/@julsimon. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering... Read More →


Tuesday June 25, 2019 09:30 - 09:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

10:00

Lessons Learned from Building a Credit Card Fraud Model
This talk covers two ML problems Stripe faced (and solved!) in building its credit card fraud detection system:

- Addressing class imbalance in training data: legitimate transactions greatly outnumber fraudulent ones, and models trained on imbalanced data often have low precision
- Performing counterfactual evaluation to measure performance in production and obtain unbiased training data when the ML system itself is constantly changing outcomes (if we block a transaction we think is fraudulent, we don’t actually know if we got it right—we have no way to observe the transaction’s ultimate outcome)

Speakers
avatar for Leela Senthil Nathan

Leela Senthil Nathan

Software Engineer, Stripe
Leela is a software engineer at Stripe, a technology company that builds economic infrastructure for the internet. She has spent two years working on various improvements to Stripe's transaction fraud models, including feature engineering, improvements to the training data generation... Read More →


Tuesday June 25, 2019 10:00 - 10:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

10:30

Expo - Networking - Coffee
Meet our exhibitors and connect with fellow attendees over coffee, tea and refreshments.

Tuesday June 25, 2019 10:30 - 11:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

Bias and bugs: implementing recommendations
After modeling and validating both with automatic and internal manual tests, we deploy a recommendation system. But did we randomize properly the testing groups? Adding a feature to one page, but not another, will already imply in selection bias. In this presentation we will quickly present a neural network based recommender, but focus on the issues faced when (a) defining our randomized trial test (b) selecting the test and control groups (c) coping with our inherent web based selection bias and (d) defining which statistical test to apply and (e) how to interpret its results.

Speakers
avatar for Guilherme Silveira

Guilherme Silveira

Head of Education, Alura
Guilherme co-founded Caelum and Alura, the largest brazilian online training platform in data science, machine learning and software development.With over 15 years of experience in software development education he is responsible for innovation, content quality and training at Alura... Read More →


Tuesday June 25, 2019 11:00 - 11:20
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

Invoice Payment to Optimize Cash Collection
Predicting invoice payment is valuable in multiple industries and supports decision-making processes in most financial workflows. This work presents a prototype developed as a solution devised during a partnership with a multinational bank to support collectors in predicting invoices payment. The proposed prototype reached up to 83.5% of accuracy, which improved the prioritization of customers and supported the daily work of collectors and we expect to support researchers dealing with the problem of invoice payment prediction to get insights and examples of how to tackle issues present in real data

Speakers
avatar for Ana Paula Appel

Ana Paula Appel

Researcher and Data Scientist, IBM Research
Ana Paula is a Research Staff Member in IBM Research - Brazil, currently work with large amount of data to do Science WITH Data and Science OF Data at IBM Research Brazil. My technical interesting are in data mining and machine learning area specially in graph mining techniques for... Read More →


Tuesday June 25, 2019 11:00 - 11:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

Training and deploying ML models with Kubeflow and TensorFlow Extended (TFX) — sponsored by CI&T
For real-world ML systems, it is crucial to have scalable and flexible platforms to build ML workflows. In this workshop, we will demonstrate how to build an ML DevOps pipeline using Kubeflow and TensorFlow Extended (TFX). Kubeflow is a flexible environment to implement ML workflows on top of Kubernetes - an open-source platform for managing containerized workloads and services, which can be deployed either on-premises or on a Cloud platform. TFX has a special integration with Kubeflow and provides tools for data pre-processing, model training, evaluation, deployment, and monitoring. In our workshop, we will demonstrate a pipeline for training and deploying an RNN-based Recommender System model using Kubeflow.

Speakers
avatar for Fábio Uechi

Fábio Uechi

ML Engineer, CI&T
I'm a passionate software craftsman working as a ML Engineer at Ci&T in Campinas. Over the past 15 years I've been involved in projects ranging from rich mobile clients and web applications through to highly scalable distributed systems. More recently I started working with the amazing... Read More →
avatar for Gabriel Moreira

Gabriel Moreira

Lead Data Scientist, CI&T
Gabriel Moreira is a Doctoral candidate at Instituto Tecnológico de Aeronáutica - ITA, researching about Deep Learning and Recommender Systems. He is also a software engineer with field experience since 2002 and speaker in international conferences. At CI&T, he leads a team of Data... Read More →
avatar for Rodrigo de Freitas Pereira

Rodrigo de Freitas Pereira

Data Scientist, CI&T
Data Scientist at CI&T. Experience and interest on machine learning modelling with TensorFlow applied for signal processing. Master’s student on Brain Computer Interface at UNICAMP.


Tuesday June 25, 2019 11:00 - 12:30
Room 7 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:30

TensorFlow image inferencing: an adventure in Python and Go
We tried to use the TensorFlow SDK in our existing Go applications, a natural fit for inference on our deep learning models. However, the Go API is not as well maintained as the Python APIs and we hit problems, extracting our inferencing into a standalone Python project.

In Python, it was easy to validate our results but we faced new challenges: do we make our communication synchronous or asynchronous? Do we use HTTP? REST? gRPC? Message queues? In this presentation we tackle several versions of this project and how we reached a stable architecture supporting many deep learning models.

Speakers
avatar for Vitor De Mario

Vitor De Mario

Tech Lead, NeuralMed
Former organizer of GopherCon Brasil and the Go meetups in São Paulo. Speaker since 2015, including TDC São Paulo and Porto Alegre, GopherCon Brasil 2016, a lightning talk on GopherCon Denver 2017, THECONF and 7Masters. Tech lead of a data science company working on deep learning... Read More →


Tuesday June 25, 2019 11:30 - 11:50
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:30

Where are the gains: Should I use A/B Tests for forecasting?
In this talk, we will analyze some theoretical aspects related to the results of an A/B test, in scenarios where Machine Learning models are involved. We will discuss the risks of taking results of an A/B test, or other purely comparative methodology, as a prediction of future gains. We will review the main practical and theoretical differences between A/B test and forecasting, when conducting ML related projects. This discussion targets a mixed audience, embracing people from technical and business areas. Also, it will be illustrated with real world examples taken from actual A/B tests.

Speakers
avatar for Eder Martins

Eder Martins

Data scientist, SEEK
Eder Martins is a senior Machine Learning engineer passionate about solving problems. Currently, he is working on ML projects related to search and recommendation for online recruitment markets at Seek AI GDP team. MSc in Computer Science at UFMG, his interests include: Recommendation... Read More →


Tuesday June 25, 2019 11:30 - 11:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

12:00

Deploy your Deep Learning models in serverless architectures
You received the task of building a Deep Learning model for detecting Malaria in human cell pictures. After this, you:
Prepared the datasets;
Chose the best architecture for the task;
Set up the training environment;
Trained the model;
Tested the model.
What now? Where should you deploy it? Will you need a GPU for inferences? What about auto-scaling? Should you build an API for it?
This presentation will show you what a Serverless Architecture is and how easily you can deploy your Deep Learning models in it, at a very low cost.

Speakers
avatar for Adriano Dennanni

Adriano Dennanni

Machine Learning Engineer, neuronio.ai
Machine Learning Engineer @ neuronio.aiGraduated in Computer Engineering @ POLI-USP/Brazil


Tuesday June 25, 2019 12:00 - 12:20
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

12:00

I know what you did last session: clustering users with ML
Understanding user behaviour is one of the main challenges of any company. In this presentation, we’ll talk about how we explored users’ activity to find common patterns among them in three important moments of the customer journey. Through our experience with this project, we hope you’ll learn a bit about how to select the right data to analyze, how to find out which data actually matters, what are the challenges facing unsupervised learning algorithms in real life, how to check if your results make sense, and how you can use the power of storytelling to communicate results.

Speakers
avatar for Adauto Braz

Adauto Braz

Data Scientist, Stoodi
Adauto Braz - graduated at Aeronautics Institute of Technology (ITA) as a computer engineering in 2018 - is a Data Scientist, currently working at the Data team at Stoodi - an education startup. At Stoodi, he’s worked with Data Engineering, Data Analysis, Data Culture and NLP.


Tuesday June 25, 2019 12:00 - 12:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

12:30

Expo - Networking - Lunch
Lunch won't be provided. You can grab something to eat with fellow attendees in the shopping center.

Tuesday June 25, 2019 12:30 - 14:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

K8s-workqueue: Simplified Kubernetes ML Batch Jobs
Managing batch ML jobs is a central competency for Data Science (DS) teams in the ad tech space. According to PWC research, digital ad spend has increased by 23% to $50 Billion in the first half of 2018. To deal with this growth, DS teams need flexible tools.
We present our k8s-workqueue system. A pluggable scheduling mechanism for ML Kubernetes workloads where tens of thousands of models are built every day on our platform. The focus on simplicity, led us to the design of this system that combines familiar features of traditional cron jobs and containers, with the power of the Kubernetes API.

Speakers
avatar for Chinmay Nerurkar

Chinmay Nerurkar

Senior Software Engineer II, Team Lead, Xandr Inc.


Tuesday June 25, 2019 14:00 - 14:20
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

Using Machine Learning to recommend jobs in User Cold Start
Industry still struggles to design recommenders able to provide useful recommendations for users who have not interacted with any item (User Cold Start scenario). In this talk, we will show how to connect new candidates to their desired jobs in one of the main online employment marketplaces in Latin America. The solution involves, first, modeling user and item profiles based on content features and then using Machine Learning to predict interactions between them. A / B testing evidenced the proposed solution is able to enhance user engagement.

Speakers
avatar for Andryw Marques

Andryw Marques

Data Scientist, SEEK
Andryw Marques is a Data Scientist at Seek-AI GDP team, currently working with projects related to Search and Recommendation for online employment. He has experience in fields such as Machine Learning, Information Retrieval and Data Analysis. Andryw received his Master and Bachelor's... Read More →


Tuesday June 25, 2019 14:00 - 14:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

Introduction to classification with SKLearn — sponsored by Caelum
You have heard and seen a few talks on machine learning but have not yet implemented anything by yourself. In this workshop we will go through a few first attempts to create classification models for situations which try to model daily life applications we are aware of.
- Practice with more than one example
- See Machine Learning in use with examples related to daily life in a company
- Understand how classification algorithms are everywhere
- Look at the results with an analytic mindset
- Compare linear and non linear algorithms
- Understand how classification algorithms work
- Create testable, repeatable experiments
- Use Support Vector Machines, Decision Trees and Dummy Classifiers

Tuesday June 25, 2019 14:00 - 15:30
Room 7 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:30

Airflow on Kubernetes: a modern approach to ETL workflows.
ETL workflows are no different from standard software. They should be implemented as code, with automated tests and continuous delivery. It should also be easy to understand, scale, debug, modify and monitor. Apache Airflow provides a framework for designing workflows as Python scripts, along with centralized logs, tasks status, metrics and a graph view. All these great features come at the price of a steep learning curve and a nasty mix of orchestration bugs and task bugs due to the variety of operators. I'll show how to use only one operator for any ETL workflow and solve that problem.

Speakers
avatar for Raphael Sampaio

Raphael Sampaio

Engineer, Konduto
Engineer at Konduto, a Brazilian company using Machine Learning for fraud detection. Our algorithm combines geographical, social and behavioral features to deliver an accurate risk measure, increasing customers profit margins while keeping fraud rates under control.


Tuesday June 25, 2019 14:30 - 14:50
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:30

A Clinical Application of Deep Learning for NLP with Word-Embeddings
Clinical coding represents the transposition of clinical findings and diagnostics into codes contained in the International Classification of Diseases (ICD). To perform such task, hospitals assign the role of “clinical coder” to the person responsible for reading the whole clinical documentation and assigning the ICD codes accordingly. This research aims to present a deep learning framework for natural language processing (NLP) capable of automating this task by interpreting (and further classifing) the text contained within these documents, by using "self-taught" word embeddings (learned from the database itself) as input.

Speakers
avatar for Arnon Santos

Arnon Santos

Data Scientist, Junto Seguros
MSc. (PUC-PR) in Computing for Health Sciences, researcher in IA and Machine Learning and member of the Brazilian Computing Society. My main research is based on the usage of Deep Learning applied to natural language processing, where I seek to expand the current state-of-art of natural... Read More →


Tuesday June 25, 2019 14:30 - 14:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

15:00

Time Series Forecasting for Cloud Resources Provisioning
Forecasting cloud resources consumption is one of the main challenges faced by IT operations teams in capacity planning tasks. Those teams often should make predictions for periods with no corresponding previous data whose cloud transactions activity changes, for instance, on a holiday. In this talk, it is discussed an approach which is able to model this future behavior with synthesized data. The procedure uses small samples to synthesize data to fit a time series forecasting model which applies interpretable parameters to be adjusted by domain knowledge analysts.

Speakers
avatar for Leonardo Neri

Leonardo Neri

AI Manager, Accenture
Leonardo has a Ph.D. in Signal Processing and Pattern Recognition. His academic research is on Speech Processing field, specialized on Speaker Diarization.He is currently working at Accenture with data science, optimization problems, natural language processing, and machine learning... Read More →


Tuesday June 25, 2019 15:00 - 15:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

15:30

Expo - Networking - Coffee
Meet our exhibitors and connect with fellow attendees over coffee, tea and refreshments.

Tuesday June 25, 2019 15:30 - 16:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

16:00

How Big Data Powers Ambev’s Sales Machine - sponsored by Big Data
Ambev visits hundreds of thousands of points of sale in Brazil every week, and needs to decide the optimal assortment and pricing for each sales call. In partnership with Brazilian AI leader Big Data, its sales process was transformed into a machine-learning powered sales machine, using thousands of variables to deliver actionable insights for sales reps, bringing significant sales growth. This session will present the real-life experience of one of the world’s largest CPG companies as it deploys the knowledge frontier at scale

Speakers
avatar for Gustavo Ioschpe

Gustavo Ioschpe

Founder & CEO, Big Data
B.S. Wharton School, Management; B.A. University of Pennsylvania, Political Science. M.A. Economics, Yale University. Founder and CEO @ Big Data, Brazil's leading applied IA company. Member of the board at Iochpe-Maxion S.A., Instituto Ayrton Senna and Conselho de Gestão da Educação... Read More →


Tuesday June 25, 2019 16:00 - 16:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

16:30

How Machine Learning is Transforming the Way iFood Runs its Logistic - sponsored by Movile
Food delivery logistics pushes the boundaries of traditional logistics with new characteristics: very short times to delivery (<40mn), the use of a cloud of drivers, and deliveries route optimization taking into account stochastic future events. IFood is reinventing the way it runs logistics with new fields of machine learning applications including the repositioning of drivers to meet demand, dynamic pricing to manage driver supply and the estimation of logistic delivery times. We will analyse in detail how models of machine learning were built and deployed at scale to estimate delivery time of arrival, and kitchen preparation times, in order to improve final customer experience and reduce logistic costs.

Speakers
avatar for Arnaud Seydoux

Arnaud Seydoux

Logistic IA manager, iFood
IA and modelling enthousiast, I graduated in evolutionary genetics, currently leading logistic IA team at iFood.


Tuesday June 25, 2019 16:30 - 16:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

17:00

Panel: Diversity in ML
ML models are known to learn from the data they are submitted. However, some problems in the models can only be accounted for when they fail to express the "impartial" perspective they were supposed to have. In this sense, to get the most benefit from advances in AI and machine learning, culture, and diversity in the teams is a critical aspect to avoid data bias in many senses. Without diverse teams, the data and the learned models may drive automation to a bias that only deepens the gap.


Speakers
avatar for Esther Colombini

Esther Colombini

AI Researcher, Advanced Institute for Artificial Intelligence
Professor of Robotics and Artificial Intelligence @ University of Campinas (Unicamp). Ph.D. and an MSc degree in Computer Engineering @ Technological Institute of Aeronautics (ITA).Bachelor on Computer Science @ Universidade Federal da Paraíba (UFPB), partially executed at Unive... Read More →
avatar for Larissa Lautert

Larissa Lautert

Data Scientist, Linx Impulse
Computer scientist working on data science. Experience in predictive models, recommender systems, ETL, A/B test evaluation and data analysis. Passionated by translating large data sets into business insights and answering questions with data. Analytical and thorough profile.
avatar for Ana Paula Appel

Ana Paula Appel

Researcher and Data Scientist, IBM Research
Ana Paula is a Research Staff Member in IBM Research - Brazil, currently work with large amount of data to do Science WITH Data and Science OF Data at IBM Research Brazil. My technical interesting are in data mining and machine learning area specially in graph mining techniques for... Read More →
avatar for Ricardo Herrmann

Ricardo Herrmann

Artificial Intelligence Engineer, Olivia AI
Ricardo Herrmann is a Computer Scientist working as an Artificial Intelligence Engineer at Olivia AI. He has 20 years of experience in the industry, having previously worked as Data Scientist at Dell EMC Consulting and as a Research Software Engineer at IBM Research Brazil, among... Read More →


Tuesday June 25, 2019 17:00 - 17:30
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

17:30

Drinks!
Stay around in the evening — drinks are on us!

Tuesday June 25, 2019 17:30 - 19:30
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil
 
Wednesday, June 26
 

08:15

Welcome & Registration
Doors open at 8.15am. We strongly recommend to arrive early in order to have time to go through security, get your PAPIs badge, choose your favorite t-shirt (we have some really cool and exclusive designs, but limited sizes), meet fellow attendees, exhibitors, and find a good seat in the auditorium. We’ll also have breakfast snacks, fruit, tea, coffee and refreshments!

Wednesday June 26, 2019 08:15 - 09:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

09:00

Ludwig, a Code-Free Deep Learning Toolbox
The talk will introduce Ludwig, a deep learning toolbox that allows to train models and to use them for prediction without the need to write code. It is unique in its ability to help make deep learning easier to understand for non-experts and enable faster model improvement iteration cycles for experienced machine learning developers and researchers alike. By using Ludwig, experts and researchers can simplify the prototyping process and streamline data processing so that they can focus on developing deep learning architectures.

Speakers
avatar for Piero Molino

Piero Molino

Senior ML / NLP Research Scientist, Uber AI Labs


Wednesday June 26, 2019 09:00 - 09:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

09:30

DataOps architecture for Machine Learning - brought to you by everis
As DataOps practices are changing the way that corporations deal with their data, there is a relevant opportunity to reduce the risk and time-to-market inherent to every Machine Learning project. However, are you ready to adopt those practices? In this presentation, you will get to know Noronha: a new open source, user-friendly framework that aims to host your projects inside a portable, ready-to-use DataOps architecture, thus helping you benefit from the most trending DataOps practices without having to change much of your usual work behavior.

Speakers
avatar for Carlos Porto Filho

Carlos Porto Filho

Data Scientist, Everis
Data scientist at Everis Brazil. I have a bachelor’s degree in Biomedical Informatics and a master’s degree in Bioengineering. I have worked in machine learning solutions in health, banking, retail and telecom.
avatar for Gustavo Castilhos

Gustavo Castilhos

Data Architect, everis
I am a Data Engineer and Architect at everis, where I assist our Machine Learning team by designing both batch and real-time pipelines that allow them to extract value of their Big Data assets with the most efficiency and automation. My latest works are focused in the engineering... Read More →


Wednesday June 26, 2019 09:30 - 09:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

10:00

AI culture and semi-autonomous review approval - sponsored by Dafiti
Dafiti Group, Latin America's biggest fashion e-commerce is on its way to become an AI-first enterprise. During this transformation it is essential to understand how to find AI opportunities throughout all Dafiti's areas and how to map such opportunities to OKRs (Objective and Key results). Under these conditions, we present in this talk as a concrete example how we created a system which evaluates - approves and rejects - user’s product reviews automatically, along with it provides a tool for easier data curation by humans, sample analysis and monitoring.


Speakers
avatar for Ricardo Savii

Ricardo Savii

Data Scientist, Dafiti Group


Wednesday June 26, 2019 10:00 - 10:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

10:30

Expo - Networking - Coffee
Meet our exhibitors and connect with fellow attendees over coffee, tea and refreshments.

Wednesday June 26, 2019 10:30 - 11:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

BERT: Multi-language approach for Q&A and NLP Applications
The advent of deep pre-trained models represents a big change in the way natural language processing is implemented. We present here a state-of-the-art technique called Bidirectional Encoder Representation of Transformers (BERT). It is as an approach to tackle the Question & Answers task as well as others NLP problems in a multi-language environment. We show the benefits and drawbacks of using such solution in real world applications.

Speakers
avatar for Horst Rosa Erdmann

Horst Rosa Erdmann

Lead Data Scientist, Everis
Computer Engineer with Master Degree in AI on FEI UniversityWith large experience in Big Data and Data Science projects.Worked in several areas in AI such as Computer Vision, Natural Language Processing, Time Series, Signal Processing, Fraud Detection among others.Joined one of the... Read More →


Wednesday June 26, 2019 11:00 - 11:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

Fklearn: A functional library for machine learning
Fklearn is a production-ready functional library for machine learning. Fklearn is already being used to power millions of predictions with significant impact on the business bottomline. While it is written in Python, it follows the best practices of functional programming, offering side-effect free machine learning pipelines. Fklearn is Pandas dataframe first, with a pragmatic choice of models. It provides advanced encoders, transformations, and realistic evaluation methods. Fklearn has continuous integration including unit tests with high coverage, linting, and static type checking.

Speakers
avatar for Henrique Lopes

Henrique Lopes

Machine Learning Engineer, Nubank
Data scientist at Nubank, working with risk models in the credit lines squad. PhD student the Unicamp, working with Bayesian deep learning and uncertainty quantification. Master's degree on adversarial images and variational autoencoders. Previously, worked as a senior data scientist... Read More →


Wednesday June 26, 2019 11:00 - 11:30
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:00

Using pre-trained models for classification where samples are scarce - sponsored by Dafiti
We present an overview of techniques that mitigate deep learning data hunger and (attempt to) leverage the power of deep learning on smaller datasets. Specifically, we will review techniques such as zero-shot learning, transfer-learning and the Transformer architecture.

Speakers
avatar for Ricardo Savii

Ricardo Savii

Data Scientist, Dafiti Group


Wednesday June 26, 2019 11:00 - 12:30
Room 7 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:30

Multitask convolutional neural networks: saving GPU time
Convolutional neural networks are great for image classification, there's no doubt about it. The problem is: each one you add to your pipeline increase processing time and require more GPU memory, which can get quite costly. We'll discuss how to deal with that by training convolutional neural networks with multiple classifiers sharing the convolutional layers. We'll evaluate the results in a dataset of apparel products, discussing impact in accuracy and on the quality of the embedding.

Speakers
avatar for Paulo Eduardo Sampaio

Paulo Eduardo Sampaio

Data science specialist, McKinsey & Company
Paulo is a civil engineer with a MBA and a MSc in statistics and operations research. He's been working with applied machine learning since 2013 and from 2015 onwards he specialised in computer vision applications. He's currently working for McKinsey as a data science specialist in... Read More →


Wednesday June 26, 2019 11:30 - 11:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

11:40

Reproducibility with Data Version Control
Data Version Control (or DVC) is a tool that complements git allowing data files to be versioned and shared easily, as well as enforcing best practices required for reproducible experiments in data science projects. Scientific methods aside, it also makes experimentation not only safer but faster. More details at https://dvc.org/

Speakers
avatar for Victor Villas Bôas Chaves

Victor Villas Bôas Chaves

Data Engineer, Gupy
Currently a Data Engineer at Gupy, the leading ATS in Brazil. Also committer of open source tools for data science and data engineering like pandas and apache airflow.


Wednesday June 26, 2019 11:40 - 12:10
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

12:00

AI informs, humans choose -- or do they?
The first expert systems were aimed at informing people so they made better decisions and depended less on hard-to-find-harder-to-pay human specialists. Now, however, with the increasing refinement of techniques, hidden layers, and ubiquity of complex systems, results are often applied as they come. Humans are not good at making decisions under risk, and in Machine Learning applications they often don't even know they're taking a rough probability as an inexorable result. So, how may we design systems that help humans make choices with healthy doses of skepticism?

Speakers
avatar for Bianca Ximenes

Bianca Ximenes

Independent consultant / Doctoral Student, Tecnora / UFPE
Bianca is a Google Expert on Product Strategy, Currently, as a Doctoral Student in Computer Science at UFPE, her work approaches human-machine boundaries and ethical repercussions of AI and ML on digital products.She enjoys reading, writing, and talking about human-AI coexistence... Read More →


Wednesday June 26, 2019 12:00 - 12:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

12:30

Expo - Networking - Lunch
Lunch won't be provided. You can grab something to eat with fellow attendees in the shopping center.

Wednesday June 26, 2019 12:30 - 14:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

Game Theory and Model Interpretability
Many machine learning models are (in)famous for being black boxes. However, model explainability is a hot topic and new techniques have been brought to life in order to overcome that. This talk will walk through how a 60+ year-old game theory concept has been adapted so that we can interpret machine learning models regardless of their inner structure and complexity — yes, neural nets and ensembles included. Most importantly, we'll talk about how you can apply this technique today in order to build better models and come up with more useful data products.

Speakers
avatar for Gabriel Cypriano Saca

Gabriel Cypriano Saca

Data Scientist, Grupo ZAP
Gabriel is currently a Data Scientist at Grupo ZAP and a Data Science Instructor at Tera. He has previously worked as a Data Scientist at Creditas and at K2 Data Science. Gabriel discovered the world of Machine Learning while co-founding Songwich, a music recommendation startup.


Wednesday June 26, 2019 14:00 - 14:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

Validating models in the real world
Validation in the real world goes way further than a random split or the K-fold. When the validation performance doesn't match the production one, there are many possible causes and a good one is that the validation was done wrongly.

On this talk, a general idea of what validation means is framed. It includes some specific cases and how to design a validation schema for them. In the end, it's expected that the audience is able to identify everything that is important when validating and how to come up with the right strategy to validate any new model they face in the Wild.

Speakers
avatar for Luis Moneda

Luis Moneda

Data Scientist, Nubank
Data Scientist at Nubank. Bachelor in economics (FEA-USP) and computer engineering (Poli-USP), MSc in Computer Science student (IME-USP). Interested in machine learning and causal inference.


Wednesday June 26, 2019 14:00 - 14:30
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:00

Everything you need to know about Tensorflow 2.0 — sponsored by Daitan
Excited about the new possibilities of Tensorflow 2.0? We are too. Come to our workshop for a hands-on experience on everything you should know about Tensorflow 2.0. We are going to show you how it works, what changed from previous versions, and of course, a highlight of the coolest features we will discuss :
  • The new Keras API: how beginners and experts can leverage the simplicity and extensibility of the Keras API
  • How to extract the maximum performance of your eager code: we will show the tf.function method, that can increase the performance of your code
  • How to export your trained model to be used in mobile devices or in the browser: with the new SavedModel structure
  • How to load your model and perform inference using Tensorflow.JS: increase your deployment options on edge machines
  • All of the above using Tensorboard and Colab notebooks

Wednesday June 26, 2019 14:00 - 15:30
Room 7 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:30

Trading strategies using deep reinforcement learning
A trader is defined as an entity that buy and sells financial instruments, while a trading strategy is a fixed plan that is designed to achieve a profitable return. The goal for the work presented here is to train a reinforcement learning agent, which is acting as the trader, to learn how to propose a good trading strategy. The agent considers not only the current information of the market but also some information of the news around the analyzed financial instrument.

Speakers
avatar for Suraj Shinde

Suraj Shinde

Director - AI Digital Lab, EVERIS MEXICO S DE RL DE CV
Suraj Shinde is Director of AI Digital Lab at everis, which is focused on research and development of artificial intelligence related technologies and solutions including developing proofs of concept, intellectual property and assets. He is also Head of everis AI in Mexico which is... Read More →
avatar for Cristyan Rufino Gil Morales

Cristyan Rufino Gil Morales

AI Research Lab Leader, everis
Self-taught person, goal-oriented, focused on AI solutions and passionate for hard challenges.Experience in the use of Reinforcement Learning algorithms and its combination with robotics. Wide experience using deep learning and machine learning models.


Wednesday June 26, 2019 14:30 - 14:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

14:40

ETL Orchestration with AWS Glue and AWS Step-functions
A demonstration showing how the Data Team at Stoodi speeded up ETL changes implementing AWS step Functions and AWS Lambda on top of AWS Glue to organize Data Pipeline as a state-machine.

On this demo we want to show how we changed a pipeline with just AWS Glue to one with two more Amazon products to ease the Pipeline modifications and improve data consistency and availability to our teams, making them more data driven. We used an AWS Lambda as main orchestration and Step-Functions as state-machine service.

Speakers
avatar for Alexsandro Francisco dos Santos

Alexsandro Francisco dos Santos

Data Engineer, Stoodi
Alexsandro Francisco is a Computer Scientist student at Federal University of ABC, Python programmer, data & A.I. enthusiast and robot maker. Already worked with Data Science, Web Scrapping and Software Development at a series of startups, learning how data can change business. Currently... Read More →


Wednesday June 26, 2019 14:40 - 15:10
Room 9 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

15:00

Attention-Based Neural Networks for Relational Data
Attention-based neural networks have recently achieved excellent performance on machine translation tasks. A 2017 NIPS paper from Google , “Attention Is All You Need”, demonstrated that attention mechanisms have the potential to replace recurrent neural networks, which are known to be computationally expensive and at times unstable. We provide a detailed example of how the same ideas can be applied to relational databases, by using attention layers which learn to condense the information present in a collection of related data tables, without the need for recurrent layers or hand-crafted features.

Speakers
avatar for Scott Brownlie

Scott Brownlie

Senior Data Scientist, TOTVS Labs
Senior Data Scientist at TOTVS Labs. Holds a BSc in Mathematics from the University of Glasgow and an MSc in Mathematics from the University of Cambridge.


Wednesday June 26, 2019 15:00 - 15:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

15:30

Expo - Networking - Coffee
Meet our exhibitors and connect with fellow attendees over coffee, tea and refreshments.

Wednesday June 26, 2019 15:30 - 16:00
Expo space Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

16:00

How Grupo ZAP is using data to empower real estate buyers, sellers, and renters in Brazil - sponsored by Grupo ZAP
Real estate in Brazil is one of the industries that lacks transparency the most. Such structure triggers a lot of dissatisfaction among all stakeholders. Grupo ZAP uses data to predict market prices, demand, and other real estate indexes that drive value, helping consumers to buy, sell, and rent faster, better, and in a more convenient way.

Speakers
avatar for Lucas Vargas

Lucas Vargas

CEO, Grupo ZAP


Wednesday June 26, 2019 16:00 - 16:20
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

16:30

Machine Learning for Natural Resources
In order to identify new exploration targets to test potential zones of gold mineralization, geologists gather different sources of data such as drill hole observations and measurements to justify their decisions. Such activity is complex and requires expert tacit knowledge specific to each mining project, meaning that the location's underlying geology is unique. With the aim of aiding this decision making process, we present a machine learning methodology to predict the level of gold mineralization based on the surrounding geological information. In particular, we propose the use of Deep Learning models, 3D Convolution Neural Networks, to take advantage of the spatial nature of the data.  Through experiments with data from a real mine, we show that our proposed model overcomes the baseline model for all the metrics used, providing a much more accurate feature for the geologists in their investigations.







Speakers
avatar for Bianca Zadrozny

Bianca Zadrozny

Research Manager, IBM
Bianca Zadrozny is a research manager at IBM Research Brazil, leading the Natural Resources Analytics group. The group's mission is to conduct research projects in knowledge-augmented machine learning for decision making in the areas of oil&gas and mining, with a great focus in developing... Read More →


Wednesday June 26, 2019 16:30 - 16:50
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

17:00

Panel: How much should we care about model interpretability?
Model interpretability is getting more and more attention both from ML practitioners and the community at large. With the GDPR and LGPD coming into force and discussions about privacy, fairness, and ethics becoming more relevant than ever, while models are getting more and more powerful with increasing complexity and opacity, how much we, as professionals and as a community, should care about model interpretability?

Speakers
avatar for Renato Vicente

Renato Vicente

Chief Scientist, Serasa Experian
A physicist interested in Machine Learning, Information Theory and Complex Systems since 1992.
avatar for Ivan Marin

Ivan Marin

Data Scientist/System Architect, Daitan Group
Physicist by training, with Masters in Applied Physics and PhD in Engineering, Ivan has experience outside the academia with applied data science, big data and architecture in different contexts, like Telcos, Healthcare, Agribusiness and other areas.
avatar for Sandor Caetano

Sandor Caetano

Chief Data Scientist, IFood / Movile
Sandor Tucakov Caetano, is an Economist (FEA-USP). Worked as a Data Scientist before it was fashionable and since 2006 built marketing, pricing and sales models for big consumer goods and food companies. Worked as the head of Data Science for a leading Fintech company and today is... Read More →


Wednesday June 26, 2019 17:00 - 17:30
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil

17:30

Closing remarks
Speakers
avatar for Ana Paula Appel

Ana Paula Appel

Researcher and Data Scientist, IBM Research
Ana Paula is a Research Staff Member in IBM Research - Brazil, currently work with large amount of data to do Science WITH Data and Science OF Data at IBM Research Brazil. My technical interesting are in data mining and machine learning area specially in graph mining techniques for... Read More →
avatar for Dan Nichol

Dan Nichol

Program Chair, AnalyticsFC
I build football data analytics tools for better recruitment at professional teams. Previously, I worked a postdoc studying the evolution of drug resistance in cancer.
avatar for Louis Dorard

Louis Dorard

General Chair, PAPIs
Louis Dorard is the author of Bootstrapping Machine Learning, of the Machine Learning Canvas, General Chair of PAPIs.io (international conferences on ML applications and APIs), and Adjunct Teaching Fellow at UCL School of Management.As an independent consultant and Machine Learning... Read More →


Wednesday June 26, 2019 17:30 - 17:45
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil