ML-foundations VS Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera

Compare ML-foundations vs Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera and see what are their differences.

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ML-foundations Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera
1 4
2,984 292
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5.4 6.3
18 days ago 11 months ago
Jupyter Notebook Jupyter Notebook
MIT License -
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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

Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera

Posts with mentions or reviews of Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing ML-foundations and Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera you can also consider the following projects:

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

Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

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

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

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

Basic-Mathematics-for-Machine-Learning - The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

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

Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.

algorithmica - A computer science textbook

coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

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

intel-processors - Datasets for All Processors Maufactured By Intel