Statistics/ Mathematical Computing Notebooks

Jupyter Notebooks on the topics of statistical analysis, mathematics, and numerical/sceintific computing (in Python).

Please feel free to connect with me on LinkedIn if you are interested in data science and like to connect.

Requirements

• Python 3.6+
• NumPy ($ pip install numpy)
• Pandas ($ pip install pandas)
• Scikit-learn ($ pip install scikit-learn)
• SciPy ($ pip install scipy)
• Statsmodels ($ pip install statsmodels)
• MatplotLib ($ pip install matplotlib)
• Seaborn ($ pip install seaborn)

Set Algebra basics

Permutations and Combinations

Probability distributions (Discrete)

Linear Regression Methods

R-style Statistical functions written using Python

Diagnostics of a linear regression problem

Introduction to hypothesis testing

Articles

Check out this article I wrote on Medium: Essential Math for Data Science.

Check out this article I wrote on Medium about "How to write your favorite R functions — in Python?"

Check out this article I wrote on Medium about "Mathematical programming — a key habit to build up for advancing in data science?"

Check out this article I wrote on Medium about "Bayes’ rule with a simple and practical example"

Check out this article I wrote on Medium about "Statistical modeling with “Pomegranate” — fast and intuitive"