QUICK GUIDE FOR DATA SCIENCE

This repository contains a quick reference guide to support data science projects. Several Python libraries are used.

A/B testing
Book - Introduction to Machine Learning with Python (Andreas C. Müller & Sarah Guido)
Introdcution to Data Science with Python - CS109x (Harvard Online)
Data Visualisation (Kaggle)

Support folders:

Name		Name	Last commit message	Last commit date
Latest commit History 173 Commits
00_cheatsheets		00_cheatsheets
00_general_notes		00_general_notes
__2025		__2025
__pycache__		__pycache__
ab_testing		ab_testing
book_hands_on_ml		book_hands_on_ml
book_int_machine_learning		book_int_machine_learning
bootcamp_ml_zoomcamp		bootcamp_ml_zoomcamp
course_intro_ml_google		course_intro_ml_google
course_mathematics_for_ml/01_linear_algebra		course_mathematics_for_ml/01_linear_algebra
data		data
data_cleaning		data_cleaning
data_science_harvard_python		data_science_harvard_python
data_vis		data_vis
img		img
projects		projects
sql		sql
statistics		statistics
ve_ml		ve_ml
.DS_Store		.DS_Store
.gitattributes		.gitattributes
.gitignore		.gitignore
README.md		README.md

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