Apache Ignite: The In-Memory Hammer in Your Data Science Toolkit

Salon B/C/D

Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers are able to find hidden insights without the help of explicit programming. These insights bring tremendous benefits into many different domains. For business users, in particular, these insights help organizations improve customer experience, become more competitive, and respond much faster to opportunities or threats. The availability of very powerful in-memory computing platforms, such as Apache Ignite, means that more organizations can benefit from machine learning today.

In this presentation we will look at some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

Speakers
Denis Magda
Denis
Magda
Product Manager
at
GridGain Systems
Denis is an expert in distributed systems and platforms who developed his skills by consistently contributing to Apache Ignite In-Memory Data Fabric and helping GridGain In-Memory Data Fabric customers build a distributed and fault-tolerant solution on top of their platform. Before joining GridGain and becoming a part of Apache Ignite community, Denis worked for Oracle Inc. where he led Java ME Embedded Porting Team helping Java opening new boundaries by entering IoT market. Currently, Denis takes the role of Product Manager in GridGain and PMC Chair in Apache Ignite, leading both products to an exciting future.
Recording