Data Science Resources
This repository contains resources and cheatsheets that will be helpful for the course (and after it!).
- Cheat Sheets - a lot of useful cheat sheets for Python, data analysis, machine learning, Git and more.
- Frequently Asked Questions - a list of links (mostly to Stack Overflow) of common questions and problems relevant to the course.
- Development Environment - development environment resources: Command Line, Git, Jupyter Notebook, etc.
- Python - basic and intermediate Python guides, tips and resources.
- Data Analysis - data analysis resources: Pandas and NumPy libraries, Exploratory Data Analysis (EDA), etc.
- Data Visualization - various data visualization guides - Pandas plotting, Matplotlib, Seaborn, Bokeh.
- Machine Learning - different machine learning guides: supervised learning (regression, classification, tree-based models etc), unsupervised learning (clustering), feature selection, model evaluation, etc.
- Natural Language Processing - Natural Language Processing resources: NLTK, SKLearn NLP and more.
- Statistics and Math - mostly optional reading for students who would like to deepen their understanding of statistics and math.
- Datasets - links to interesting datasets.