PAPIs Latam 2019 has ended

Create Your Own Event

PAPIs Latam 2019

Tais Cristina da Silva

Fatec Santos
Estudante
São Paulo Area, Brazil

08:15 GMT-03

Welcome & Registration Expo space

09:00 GMT-03

Opening remarks Room 8Dan Nichol • Ana Paula Appel • Louis Dorard

09:30 GMT-03

Reinforcement Learning for devs: toolkits, and application to autonomous race cars Room 8Julien Simon

10:00 GMT-03

Lessons Learned from Building a Credit Card Fraud Model Room 8Leela Senthil Nathan

10:30 GMT-03

Expo - Networking - Coffee Expo space

11:00 GMT-03

Training and deploying ML models with Kubeflow and TensorFlow Extended (TFX) — sponsored by CI&T Room 7Fábio Uechi • Gabriel Moreira • Rodrigo de Freitas Pereira

12:00 GMT-03

I know what you did last session: clustering users with ML Room 8Adauto Braz

12:30 GMT-03

Expo - Networking - Lunch Expo space

14:00 GMT-03

K8s-workqueue: Simplified Kubernetes ML Batch Jobs Room 9Chinmay Nerurkar

15:30 GMT-03

Expo - Networking - Coffee Expo space

16:00 GMT-03

How Big Data Powers Ambev’s Sales Machine - sponsored by Big Data Room 8Gustavo Ioschpe

17:00 GMT-03

Panel: Diversity in ML Room 8Esther Colombini • Larissa Lautert • Ana Paula Appel • Ricardo Herrmann

17:30 GMT-03

Drinks! Expo space

08:15 GMT-03

Welcome & Registration Expo space

09:00 GMT-03

Ludwig, a Code-Free Deep Learning Toolbox Room 8Piero Molino

09:30 GMT-03

DataOps architecture for Machine Learning - brought to you by everis Room 8Carlos Porto Filho • Gustavo Castilhos

10:30 GMT-03

Expo - Networking - Coffee Expo space

11:00 GMT-03

BERT: Multi-language approach for Q&A and NLP Applications Room 8Horst Rosa Erdmann Fklearn: A functional library for machine learning Room 9Henrique Lopes

11:30 GMT-03

Multitask convolutional neural networks: saving GPU time Room 8Paulo Eduardo Sampaio

12:00 GMT-03

AI informs, humans choose -- or do they? Room 8Bianca Ximenes

12:30 GMT-03

Expo - Networking - Lunch Expo space

14:00 GMT-03

Validating models in the real world Room 9Luis Moneda

15:00 GMT-03

Attention-Based Neural Networks for Relational Data Room 8Scott Brownlie

15:30 GMT-03

Expo - Networking - Coffee Expo space

16:30 GMT-03

Machine Learning for Natural Resources Room 8Bianca Zadrozny

17:00 GMT-03

Panel: How much should we care about model interpretability? Room 8Renato Vicente • Ivan Marin • Sandor Caetano

17:30 GMT-03

Closing remarks Room 8Ana Paula Appel • Dan Nichol • Louis Dorard