Apache Spark for machine learning and data science
The Data Science with Apache Spark workshop will show how to use Apache Spark to perform exploratory data analysis (EDA), develop machine learning pipelines, and use the APIs and algorithms available in the Spark MLlib DataFrames API. It is designed for software developers, data analysts, data engineers, and data scientists.
Data science & advanced analytics, Machine Learning
Machine learning with TensorFlow
Robert Schroll (The Data Incubator)
Robert Schroll demonstrates TensorFlow's capabilities through its Python interface and explores TFLearn, a high-level deep learning library built on TensorFlow. Join in to learn how to use TFLearn and TensorFlow to build machine-learning models on real-world data.
Big data and the Cloud, Stream processing and analytics
Architecture, Cloud, Streaming
Real-time Systems with Spark Streaming and Kafka
Jesse Anderson (Big Data Institute)
To handle real-time big data, you need to solve two difficult problems: how do you ingest that much data and how will you process that much data? Jesse Anderson explores the latest real-time frameworks (both open source and managed cloud services), discusses the leading cloud providers, and explains how to choose the right one for your company.
Cloudera Big Data Architecture Workshop
Bruce Martin (Cloudera)
The Cloudera Big Data Architecture Workshop (BDAW) is a 2-day leaning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system.