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HackerMath for Machine Learning

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The following topics are covered at the workshop:

Module 1: Basics of Statistics (Application: A/B Testing)
Module 2: Basics of Linear Algebra (Application: Supervised Machine Learning: Linear Regression)
Module 3: Basics of Linear Algebra -continued (Application: Unsupervised Machine Learning: Dimensionality Reduction)

Installation Instructions

We would be using Python data stack for the workshop.

Please refer to the installation instructions document. That document also has instructions on how to run a script to check if the required packages are installed.

Basics of Python

Attendees are advised to learn basics of Python before attending the workshop. At the bare minimum, attendees should be knowing Sections 1 through 5.1 in this book: http://anandology.com/python-practice-book/


Authors:

Amit Kapoor

Bargava Subramanian

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