free 2 evening Workshop: Data Science with H2O (with Industrial IoT)

Workshop; Data Science with H2O (with Industrial IoT)

I am pleased to announce an exciting working on Data Science with H2O. This two-evening workshop is part of my course in Data Science for IoT (and also related to my course in Oxford)

The workshop will have extra places – and it is free to attend

If you are interested, please signup and I will confirm places by 23 September

Also be adding more use cases especially on IoT

Date: Sep 27 and 28 : 6:30 to 8:30

Prerequisites

R

Basic understanding of supervised learning (e.g. Random Forest, GBM)

Basic understanding of unsupervised learning (e.g. K-Means) –

Introduction to H2O and Machine Learning Use Cases (http://www.slideshare.net/JofaiChow/h2o-machine-learning-use-cases)

Schedule:

Day 1 H2O Basics (90 mins)

Importing data from different sources - data exploration - training models - supervised learning - unsupervised learning - using model for predictions

Day 2 - Advanced Topics (90 mins)

tuning models - manual tuning - full grid search - random grid search - stacking models - saving / loading models - exporting models

Software to Download and Install

· You will need R (ideally 3.3.0+) and an IDE (e.g. RStudio) - Java 1.7 or 1.8 (for H2O) - After that, you can use this script (https://github.com/h2oai/h2o-meetups/blob/master/2016_09_02_Budapest_Meetup_satRday/satRday_workshop/step_01_install_packages.R)

· to install all the necessary R packages for H2O

GitHub repo – we are using

https://github.com/h2oai/h2o-meetups/tree/master/2016_09_02_Budapest_Meetup_satRday/satRday_workshop

Note that this will be enhanced over the next week esp with IoT (anomaly detection use cases)

Presenters

Jo-Fai from H2O and Ajit Jaokar(IoT)