sylvaticus / MITx_6.86xLinks
Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning
☆333Updated 2 years ago
Alternatives and similar repositories for MITx_6.86x
Users that are interested in MITx_6.86x are comparing it to the libraries listed below
Sorting:
- Python code written for MIT's Machine Learning course offered on edX☆125Updated 6 years ago
- Introduction to ML packages for the 6.86x course☆404Updated 5 years ago
- Notes for 18.6501x, Fundamentals of Statistics on edX☆96Updated 3 years ago
- Data Analysis: Statistical Modeling and Computation in Applications☆61Updated 4 years ago
- MITx 6.86x | Machine Learning with Python | From Linear Models to Deep Learning☆55Updated 4 years ago
- Community based cheatsheet for the MITx course 18.6501x Fundamentals of Statistics☆44Updated 5 years ago
- Project code for MIT MOOC 6.86x on edX☆15Updated 5 years ago
- Fundamentals of Statistics☆45Updated 4 years ago
- An in-depth exploration to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-o…☆10Updated 6 years ago
- Probability - The Science of Uncertainty and Data☆123Updated 7 years ago
- Code of the solutions of the Mathematics for Machine Learning course taught in Coursera.☆153Updated 4 years ago
- MITx: 6.86x Machine Learning with Python: from Linear Models to Deep Learning☆16Updated 6 years ago
- Supplemental resources for courses in the MITx MicroMasters Program in Statistics and Data Science☆47Updated 4 years ago
- EdX course from MIT on machine learning 6.86x☆11Updated 5 years ago
- CheatSheet for 18.6501x☆26Updated 6 years ago
- ☆121Updated 3 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆300Updated 5 years ago
- Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.☆189Updated last year
- An Introduction to Statistical Learning with Applications in PYTHON☆557Updated 4 years ago
- A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python☆154Updated 10 months ago
- CheatSheet for 6.431x☆16Updated 5 years ago
- Exercises and solutions to Stanford CS229 Machine Learning in Python☆211Updated 2 years ago
- My own notes, implementations, and musings for MIT's graduate course in machine learning, 6.867☆350Updated last year
- Machine Learning with Python (url: https://courses.edx.org/courses/course-v1:MITx+6.86x+1T2020/course/)☆45Updated 5 years ago
- quasi-open-source introductory book about machine learning, emphasis on geometry and modern concepts☆18Updated 2 years ago
- ☆145Updated 4 years ago
- Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhur…☆246Updated last year
- Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.☆346Updated last year
- STAT 451: Intro to Machine Learning @ UW-Madison (Fall 2020)☆451Updated last year
- Repo for Statistical Learning course offered by Stanford University☆50Updated 6 years ago