Helpful Resources for Students of data science and modeling and data analysis
- Python Crash Course (book)
- Learn Python the Hard Way
- COGS 18 Materials notes; textbook
- matplotlib cheat sheets - these are really handy to have on your machine ready to go. Great references.
- Getting Started with git
- GitHub Guide
- GitHub Desktop App Tutorial
- Git Command Line Resource
- Using
gitfrom the command line- Installing and using
git(Part 1), by TA Ganesh (youtube, 22min tutorial) - merge conflicts and branching (Part 2), by IA Shubham Kulkarni (youtube, 8min tutorial)
- Installing and using
- Using
gitwith GitHub Desktop, by TA Sidharth Suresh (youtube, 13min tutorial) - GIT & GITHUB TUTORIAL, from edureka!
- with notes from TA Holly(Yueying Dong)
- Personal Access Token Tutorial by IA-ish(?) Scott Yang
- Uh oh! My Jupyter notebook has loads of big images/plots and it is now too big to fit inside Github's file size limit. - https://pypi.org/project/ipynbcompress/
- Data to Viz - help determining what visualization is appropriate; with code examples
- Kaggle's learn
pandas- for learningpandas(interactive programming) - Python Data Science Handbook (book)
- Essential Cheat Sheets for Machine Learning and Deep Learning Engineers
- Python for Data Analysis(book)
- Learning Pandas
- NLP in Python (youtube video)
- MIT's Intro to Deep Learning, course
- Mathematical Underpinnings, video from Andrew Ng
- Keras & TensorFlow, video
- Resources in ML, DL, RL, and NLP
- https://www.nationalacademies.org/our-work/the-science-of-team-science
- https://research.upenn.edu/resources/hub/team/managing/
- https://doresearch.stanford.edu/resources-collaboration-and-team-science
- https://www.socra.org/blog/cultivating-an-effective-research-team-through-application-of-team-science-principles/
- https://www.ncbi.nlm.nih.gov/books/NBK310381/
- https://en.wikipedia.org/wiki/Science_of_team_science
- https://hbr.org/2018/10/managing-a-data-science-team