H2O is machine learning global open source project - based in Silicon Valley.
We organize presentation event by H2O's Avkash who is traveling from the U.S.
We will discuss about machine learning innovation from the viewpoint of Silicon Valley. + Networking beer party.
- Machine Learning with H2O
Presenter; Avkash from H2O
Casual talk session - What is happening in Silicon Valley & What is the future of AI.
Q&A from Audience (you can send me in advance; https://twitter.com/ishiid )
20:00-21:30 - Networking Party at Craft Beer Bar (1min our office) http://www.oltokyo.jp/ (cash on delivery / entrance free / drink from 400-600yen)
This time, we have special guest from Silicon Valley - Avkash from H2O.ai!!!
Avkash brings enterprise level expertise in distributed systems, architecture, web-scale analytics, big data, machine learning and high-performance computing.
Prior joining to H2O, Avkash worked at Microsoft, Platfora and his own operation analytics startup Big Data Perspective, where he successfully shipped various enterprise and cloud applications.
At H2O, Avkash is responsible for building enterprise-ready machine learning applications, helping customers be successful using H2O products and create vibrant communities.
H2O.ai emerged in 2011 from a grassroots culture of data transformation.
Our goal was to democratize data science by making scalable machine learning open source and accessible to everyone.
With H2O, the main product, a plethora of machine learning models (from linear models to tree-based ensemble methods to Deep Learning) can be trained from R, Python, Java, Scala, JSON, H2O’s Flow GUI, or the REST API, on laptops or servers running Windows, Mac or Linux, in the cloud or on premise, on clusters of up to hundreds of nodes, on top of Hadoop or with the Sparkling Water API for Apache Spark.
H2O also features the fastest distributed data ingest and data munging capabilities, and a multitude of enterprise features such as security, authentication, model comparison and rapid deployment. Today, H2O is used by over 100,000 data scientists and more than 10,000 organizations around the world.