Implementations in python of methods and programming assignments of course Machine Learning of Coursera by Andrew Ng

susilvaalmeida Last update: Mar 04, 2024

Machine Learning with Andrew Ng

Programming assignments that I implemented in python of Coursera's Machine Learning Course (it uses Octave/MATLAB). I also added some concepts and formulas that I think are useful to help to understand the algorithms.

In order to have a nice visualization of the concepts, formulas, codes and exercises, I did all the implementations in Jupyter Notebooks.

Programming Assignments Notebooks:

Programming Exercise 1 - Linear Regression
Programming Exercise 2 - Logistic Regression
Programming Exercise 3 - Multi-class Classification and Neural Networks
Programming Exercise 4 - Neural Networks Learning
Programming Exercise 5 - Regularized Linear Regression and Bias vs Variance
Programming Exercise 6 - Support Vector Machines
Programming Exercise 7 - K-Means Clustering and Principal Component Analysis
Programming Exercise 8 - Anomaly Detection and Recommender Systems

Tags:

andrew-ng-course

andrew-ng-machine-learning

machine-learning

python

Owner

susilvaalmeida

GitHub Repository https://github.com/susilvaalmeida

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