Harvard-IACS / 2021-CS109ALinks
☆143Updated 4 years ago
Alternatives and similar repositories for 2021-CS109A
Users that are interested in 2021-CS109A are comparing it to the libraries listed below
Sorting:
- A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python☆151Updated 9 months ago
- Probably the best curated list of data science books in Python☆421Updated last month
- Cracking the Data Science Interview☆361Updated 6 years ago
- A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.☆169Updated last year
- A roadmap for those looking to start or expand a career in the data community☆304Updated 4 months ago
- 🍧 DataCamp data-science and machine learning courses☆405Updated last year
- Practical guidance for time series analysis in Python☆316Updated 4 months ago
- Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt☆216Updated 2 weeks ago
- This repository is a supplement to the 'Machine Learning Simplified: A Gentle Introduction to Supervised Learning' book.☆431Updated last year
- Python Data Analysis, Third Edition, Published by Packt☆208Updated 2 weeks ago
- Official Repo for the Efficient Python for Data Scientists Book. You can buy the book from here:☆582Updated 10 months ago
- Data Science Projects☆53Updated 5 years ago
- All content related to machine learning from my blog☆116Updated 3 years ago
- Fundamental Python workshop, proudly presented by the UCL Data Science Society☆47Updated 4 years ago
- Machine learning and deep learning resources☆556Updated 2 weeks ago
- ☆120Updated 3 years ago
- ☆50Updated this week
- Friendly link to all of my medium articles☆178Updated last year
- Practical Full-Stack Machine Learning☆706Updated 2 years ago
- Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.☆345Updated last year
- Code for the book "Software Engineering for Data Scientists"☆116Updated 2 months ago
- Middlesex University Dubai: MSc Data Science. Modelling, Regression and Machine Learning track. Instructor: Dr. Ivan Reznikov☆80Updated 2 years ago
- Learning Statistics is one of the most Important step to get into the World of Data Science and Machine Learning. Statistics helps us to …☆189Updated 2 years ago
- Hands-On Data Preprocessing in Python, published by Packt☆206Updated 2 weeks ago
- ☆143Updated 2 weeks ago
- Python-based Jupyter notebooks, notes, and project solutions from DataCamp courses on data science, machine learning, and statistics.☆93Updated last week
- Python Feature Engineering Cookbook, published by Packt☆485Updated 2 weeks ago
- Machine Learning Materials☆52Updated last year
- Errata and code for Effective Pandas book☆370Updated 3 years ago
- An Introduction to Statistical Learning with Applications in PYTHON☆555Updated 3 years ago