GDG DataFest 2018
as the organisers put it
O Data Fest é o maior evento do interior de São Paulo voltado para a disseminação do conhecimento a respeito de big data, armazenamento e processamento dados (data) e assuntos relacionados.
| title | author | length |
|---|---|---|
| Recommender Engines - What are they? Where do they live? What do they feed on? | Ahirton "Einstein" Lopes | 32m |
Overview of recommender systems: what they are, where they’re used (movies, music, news, books, search results, products) and how they work. Presents… | ||
| Provenance analysis against fake news | Alexandre Melo | 31m |
The talk describes the FAPESP DéjàVu project, which uses machine learning and computer vision to organize and reconstruct events from text, images and video to… | ||
| BigQuery/BigData. Programming with purpose | Alline Oliveira | 38m |
The talk examines when to use strong, rigid schemas versus more flexible approaches for BigQuery/Big Data pipelines, questioning whether strict relational keys… | ||
| Shall We Talk About Data Pipelines? | Cesar Nogueira | 38m |
Shows how to build automated data pipelines using Google Dataflow and BigQuery, implemented with the Dataflow SDK and Apache Beam. Describes scheduling those… | ||
| Musical Audience Index: the scientific side of the SóTocaTop program | DANIEL CUKIER | 34m |
Presents a Musical Audience Index that combines music-computation tools, cloud infrastructure, and data-science methods to produce a single popularity score… | ||
| Building a Big Data environment with Spark integrated with R on Azure | Diego Nogare | 42m |
Shows how to build an Apache Spark Big Data environment on Azure by provisioning a VM and configuring Spark to work with the R language. Covers integrating… | ||
| Apache Spark Structured Stream: A Near-Real-Time Data Grinder | Eiti Kimura | 01h 01m |
Apache Spark Structured Streaming is presented as a scalable, simple API for near-real-time processing and transformation of large transaction volumes. The… | ||
| Deploying Machine Learning Models in Serverless Architectures | Felipe Santos | 26m |
Describes how to build, validate and deploy machine learning models to production using serverless cloud architectures (functions-as-a-service). Covers the… | ||
| From Academia to Industry: Computer Vision with Deep Learning | Fernanda Andaló | 37m |
Covers teaching computers to see and interpret the world using deep learning-based computer vision, highlighting how increased data availability is changing… | ||
| Big Data Science on Google Cloud | Fernando Ultremare | 44m |
Overview of Google Cloud tools for data science and engineering, highlighting the main platforms and the newest features available for Big Data workflows on… | ||
| Handling a flood of requests with API Gateway + Lambda + Kinesis | Flavio Pimenta | 28m |
Shows how to handle very high request and data volumes using serverless AWS components—API Gateway, AWS Lambda, and Amazon Kinesis—focusing on architecture and… | ||
| Recommendation Systems without the fuss | Gabriel Moreira | 40m |
Practical introduction to recommendation systems covering core techniques and recent deep learning architectures. Includes hands-on examples in Python using… | ||
| Integrating Machine Learning - from ingestion to persistence | Hugo Rozestram | 50m |
Discusses integrating machine learning into a Big Data pipeline by using parallel ingestion and streaming tools to perform analyses earlier in the flow and… | ||
| nothing matches | ||