the-elements-of-statistical-learning VS ML-foundations

Compare the-elements-of-statistical-learning vs ML-foundations and see what are their differences.

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 (by maitbayev)
Machine Learning Statistics Python Python3 jupyter-notebook statistical-learning textbook
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ML-foundations

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science (by jonkrohn)
Machine Learning Data Science Python Mathematics Linear Algebra calculus Probability Statistics computer-science Data structures Numpy Pytorch Tensorflow jupyter-notebook
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the-elements-of-statistical-learning ML-foundations
1 1
397 2,945
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1.8 5.1
about 2 years ago 10 days ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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the-elements-of-statistical-learning

Posts with mentions or reviews of the-elements-of-statistical-learning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2020-12-31.

ML-foundations

Posts with mentions or reviews of ML-foundations. We have used some of these posts to build our list of alternatives and similar projects.
  • Worried about Calculus
    1 project | /r/OMSA | 1 Apr 2023
    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?

When comparing the-elements-of-statistical-learning and ML-foundations you can also consider the following projects:

ISL-python - Porting the R code in ISL to python. Labs and exercises

2D-Gaussian-Splatting - A 2D Gaussian Splatting paper for no obvious reasons. Enjoy!

ISLR - Introduction to Statistical Learning

Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes

homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

wordlescraper - Combine wordle statistics metrics from various locations, data science to correlate scores with words, and a front end to display the results.

Sharing_ISL_python - An Introduction to Statistical Learning with Applications in PYTHON

ITC - Computer Science coursework and projects at Tec de Monterrey 👨‍🎓

College-Work - Assignment Solutions

algorithmica - A computer science textbook

Python-Bible - Resourceful Python Collection

Reinforcement_Learning - RL Algorithms with examples in Python / Pytorch / Unity ML agents

the-elements-of-statistical-learning vs ISL-python ML-foundations vs 2D-Gaussian-Splatting the-elements-of-statistical-learning vs ISLR ML-foundations vs Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera the-elements-of-statistical-learning vs homemade-machine-learning ML-foundations vs wordlescraper the-elements-of-statistical-learning vs Sharing_ISL_python ML-foundations vs ITC the-elements-of-statistical-learning vs College-Work ML-foundations vs algorithmica the-elements-of-statistical-learning vs Python-Bible ML-foundations vs Reinforcement_Learning