greyhatguy007/Machine-Learning-Specialization-Coursera
Stanford's ML Specialization, Filled Out in Jupyter
Complete solved notebooks and notes for Andrew Ng's 2022 Machine Learning Specialization on Coursera, mapped week-by-week to the curriculum.
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What it does This repo is a curated index of solved Jupyter notebooks, practice quizzes, and programming assignments for Andrew Ng’s Machine Learning Specialization on Coursera. It tracks the curriculum week by week, covering linear and logistic regression, neural networks in TensorFlow and NumPy, and related concepts. In practice, it functions as a heavily annotated answer key you can actually run.
The interesting bit The README is little more than a massive table of contents, but that austerity is the point: every optional lab, gradient-descent exercise, and scikit-learn benchmark is cross-referenced and ready to diff against your own broken vectorization. It is thorough to the point of obsession.
Key highlights
- Maps the entire Machine Learning Specialization curriculum week by week, from regression to neural networks
- Includes both from-scratch NumPy implementations and high-level TensorFlow labs
- Optional labs cover feature scaling, regularization, overfitting, and decision boundaries
- Links to a companion mathematics repo for the underlying linear algebra and calculus
- 7,536 stars and counting, suggesting it serves as the de facto class notes
Caveats
- The README is essentially a bare index of notebook links with minimal narrative explanation
- A few duplicate links point to the same file under different labels (e.g.,
C1_W2_Lab05_Sklearn_GD_Soln.ipynbappears twice in Course 1, Week 2)
Verdict A useful crutch for anyone currently enrolled in the specialization and debugging a lab that will not converge. Everyone else can safely skip it unless they are nostalgic for 2022-era introductory ML coursework.
Frequently asked
- What is greyhatguy007/Machine-Learning-Specialization-Coursera?
- Complete solved notebooks and notes for Andrew Ng's 2022 Machine Learning Specialization on Coursera, mapped week-by-week to the curriculum.
- Is Machine-Learning-Specialization-Coursera open source?
- Yes — greyhatguy007/Machine-Learning-Specialization-Coursera is open source, released under the MIT license.
- What language is Machine-Learning-Specialization-Coursera written in?
- greyhatguy007/Machine-Learning-Specialization-Coursera is primarily written in Jupyter Notebook.
- How popular is Machine-Learning-Specialization-Coursera?
- greyhatguy007/Machine-Learning-Specialization-Coursera has 7.7k stars on GitHub.
- Where can I find Machine-Learning-Specialization-Coursera?
- greyhatguy007/Machine-Learning-Specialization-Coursera is on GitHub at https://github.com/greyhatguy007/Machine-Learning-Specialization-Coursera.