Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
 
Capital Suite 7
Add Data science for managers to your personal schedule
9:00 Data science for managers Angie Ma (ASI)
Capital Suite 17
Add Machine learning with TensorFlow to your personal schedule
9:00 Machine learning with TensorFlow Dana Mastropole (The Data Incubator)
Capital Suite 16
Add Real-time systems with Spark Streaming and Kafka to your personal schedule
9:00 Real-time systems with Spark Streaming and Kafka Jesse Anderson (Big Data Institute)
S11C
Capital Suite 1
London Suite 2
Add Hands-on data science with Python to your personal schedule
9:00 Hands-on data science with Python Rich Ott (The Data Incubator)
London Suite 3
Add Machine learning with PyTorch to your personal schedule
9:00 Machine learning with PyTorch Delip Rao (R7 Speech Science)
10:30 Coffee break | Room: Capital Suite Foyer
12:30 Lunch | Room: Capital Suite Foyer
15:00 Afternoon break | Room: Capital Suite Foyer
9:00-17:00 (8h)
Data science for managers
Angie Ma (ASI)
Angie Ma offers a condensed introduction to key data science and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization.
9:00-17:00 (8h)
Machine learning with TensorFlow
Dana Mastropole (The Data Incubator)
Dana Mastropole demonstrates TensorFlow's capabilities through its Python interface and explore 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.
9:00-17:00 (8h)
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.
9:00-17:00 (8h) Data science and machine learning
Apache Spark programming
The instructor walks you through the core APIs for using Spark, fundamental mechanisms and basic internals of the framework, SQL and other high-level data access tools, and Spark’s streaming capabilities and machine learning APIs.
9:00-17:00 (8h)
Data science and machine learning with Apache Spark
behzad bordbar (Cloudera)
Behzad Bordbar demonstrates how to implement typical data science workflows using Apache Spark. You'll learn how to wrangle and explore data using Spark SQL DataFrames and how to build, evaluate, and tune machine learning models using Spark MLlib.
9:00-17:00 (8h)
Hands-on data science with Python
Rich Ott (The Data Incubator)
Rich Ott offers a foundation in building intelligent business applications using machine learning, walking you through developing a machine learning pipeline from prototyping to production. You'll learn about data cleaning, feature engineering, model building and evaluation, and deployment and then use this knowledge to create two example applications from real-world datasets.
9:00-17:00 (8h)
Machine learning with PyTorch
Delip Rao (R7 Speech Science)
PyTorch is a recent deep learning framework from Facebook that is gaining massive momentum in the deep learning community. Its fundamentally flexible design makes building and debugging models straightforward, simple, and fun. Delip Rao walks you through PyTorch's capabilities and demonstrates how to use PyTorch to build deep learning models and apply them to real-world problems.
10:30-11:00 (30m)
Break: Coffee break
12:30-13:30 (1h)
Break: Lunch
15:00-15:30 (30m)
Break: Afternoon break