Introduction_to_statistical_learning_summary_python
ML-foundations
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1 | 1 | |
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10.0 | 5.4 | |
almost 2 years ago | 26 days ago | |
Jupyter Notebook | Jupyter Notebook | |
- | MIT License |
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Introduction_to_statistical_learning_summary_python
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Can you recommend a Python textbook to replace "An Introduction to Statistical Learning with Applications in R", Witten, J. et. al. [E]
There is Python code available for that book.
ML-foundations
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Worried about Calculus
As others have said, you won't need calculus immediately, but it's important that you make a good attempt at learning up to Calc3. I also didn't have a math heavy undergrad so it took a lot of self-study for me, but it's possible. Simulation has a great math boot camp at the beginning to review everything but you'll want to be prepped with Calc before that because that class is all calculus based probability. Some other good resources are the 3Blue1Brown videos on YouTube. They have a great series for both calc & linear algebra to talk through all the intuition with visuals. I also really like John Krohns series because you code through the math which is very applicable for us in this program. I only did his linear Algebra, but he has a whole series with Calc and probability, too. https://github.com/jonkrohn/ML-foundations
What are some alternatives?
Statistics-and-probability - Statistical concepts, from statistical inference to Bayes probability and different distribution types
2D-Gaussian-Splatting - A 2D Gaussian Splatting paper for no obvious reasons. Enjoy!
datacamp - 🍧 DataCamp data-science and machine learning courses
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
An-Introduction-to-Statistical-Learning - This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
wordlescraper - Combine wordle statistics metrics from various locations, data science to correlate scores with words, and a front end to display the results.
the-elements-of-statistical-learning - My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
ITC - Computer Science coursework and projects at Tec de Monterrey 👨🎓
algorithmica - A computer science textbook
Reinforcement_Learning - RL Algorithms with examples in Python / Pytorch / Unity ML agents
intel-processors - Datasets for All Processors Maufactured By Intel
linear-regression-from-scratch - A data science project for part II physics project E (surveying using stars)