Resources

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Getting Started with Applied Data Science with Venture Applications:

  • See this Github link for install instructions for all necessary tools including install examples in Jupyter Notebook format


Course Materials:

Visit Github for Lectures Materials (Click Here) 

  • Course Introduction: download from Github here
  • Starting Fall 2017, all lectures and code samples will be available at this Github Repository


Coding Questions: Try Stack Overflow and/or simply ask Google

CS Tools Reference Materials:
Ref CS01:  Python 3 Quick Reference (download) (weblink), Python 2.7 Quick Reference
and Python Data Structures for 2.7.
Ref CS02: NumPy Getting Started v1-12
Ref CS03: Pandas in 10 Min
Ref CS04: Pandas-SciPy-Numpy-Cheatsheet
Ref CS05: TensorFlow Getting Started
Ref CS06: SciKitLearn Reference Guide, Algorithm Cheat Sheet
Ref CS07: MatPlotLib Guide
Ref CS08: JSON File Format, JSON Examples

Math Reference List:
Ref M01: Covariance and Correlation
Ref M02: Basic Matrix Math
Ref M03: Gradient Descent
Ref M04: Linear-vs-Logit
Ref M05: Regression Analysis
Ref M06: Markov Chains (simplified)(complete) (Wikipedia)

Extra Reading & Online Courses:
Ref EROC01 (free): Book: Introduction to Statistical Learning
Ref EROC02: Book: Hands-On Machine Learning with Scikit-Learn and TensorFlow
Ref EROC03: MOOC: Machine Learning, Coursera
Ref EROC04: DataCamp —- Sign up here for free classes (Open until Oct25th)