Practical ML on H2O

This coursera course provides a way to utilize H2O for applying Machine Learning Purposes. Note, this course has more focus on application and that on H2O.

However, having said that, anyone doesn't require an in-depth pre-req of H2O. I think it is good to have a glance and to understand the basics of ML in H2O but if one is looking in theory, then this ain't the course.

I. Week-1

    - Fundamentals

        - Pre-req and basics

II. Week-2

    - Trees and Overfitting

        - Tree algorithms

        - Importing, generating and Over-fitting

III. Week-3

    - Linear Models and More

        - Loading and Saving

        - Linear Models and Naive Bayes

        - Data Manipulation

        - Grids

IV. Week-4

    - Deep Learning

        - Early stopping

        - Binning and Merging

        - Deep learning

V. Week-5

    - Unsupervised learning

        - Autoencoders

        - More dimensional redution

        - Clustering

        - Handling missing data

V. Week-6

    - Other

        - Ensembles

        - Other H2O technologies

Click here to access the python notebook with codes (and assignments)

Click here to read the quizzes

Other references found online [1]