• 31/05/2016

Meetup: Data Science BH - Worldsense

Participe do Meetup do BehaveData para Data Scientists.

Nosso objetivo é reunir profissionais, entusiastas e estudantes da área para discutir e debater a tecnologia, sua aplicações, e os impactos na sociedade e no mercado. Entre os principais tópicos de interesse estão: mineração de dados, visualização, aprendizado de máquina, cloud computing e big data.

A próxima edição do meetup acontecerá no dia 31 de Maio de 2016, no escritório da Thoghtworks e contará com as seguintes palestras:

Programação

Large Scale Machine Learning

Pedro Calais e Thiago Akio

WorldSense uses large-scale machine learning to suggest linksto online publishers aiming to increase the revenue they make fromtheir content. In this talk we’ll describe how we leverage Apache Spark and other popular open source tools to power our machine learning pipeline in a distributed cloud infrastructure, which include: how we train and build our models, how we monitor model quality over time, and how we’ve been experimenting with large-scale text-based deep learning models to suggest great links.

Pedro holds a doctorate degree from UFMG’s Computer Science Department.His research interests are in machine learning, data mining, social networks andconnecting social sciences and social psychology theories to algorithms that process big data. As a software engineer in WorldSense, he is loving working in applied research in the industry.

Thiago holds an engineering degree in Control and Automation from UFMG’s engineering school. Has researched about Fault Detection and Diagnosis in industrial plants using machine learning and statistical inference techniques, and is currently interested in machine learning for text/natural language processing for his master’s degree. He is excited to be able to learn about and apply the state-of-the-art algorithms within WorldSense.

Lightning Talks

Andressa Sivolella

Algoritmos Ensemble com Árvores de Decisão

Péterson Sampaio

Bancos de dados em grafos e Neo4j

Isaias Barroso Excel e Data Science, Parte II

João Fábio

Modelo Matemático para Otimização de Rotas de Ônibus com Dados Coletados por IoT

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