hathawayj / guide_MLLib

ML with Databricks: MLlib and sklearn

Presented by The Chosen

Overview

Slides

• https://esther-tang-zeon.github.io/guide_MLLib/#1

Notebooks to use during presentation

Download all these dbc files and upload them to your Databricks Community Edition. We'll work on them during our presentation.

• Classification
• Regression

Notebooks with solutions

These notebooks are the completed version of the notebooks above. Please, only refer to them after you've put enough effort to complete the exercises present in the notebooks to use during presentation.

• Classification

• Regression

  Try it Yourself

  After the presentation if you want to try using MLlib for yourself use this notebook. TryItYorself

Sources

Refer to these sources to learn more about MLlib and sklearn (Sources Also Cited in Notebooks):

• Data Used in Notebooks
• Iris Data
• Housoing Data
• Tuning the hyper-parameters of an estimator in sklearn
• What is Regression
• MLlib Regression Algorithms
• GBT Regressor
• Pipeline Documentation
• Hyperparameter Tuning for ML Models