This is my personal learning record for the famous Machine learning course in Coursera taught by Andrew ng.
While I had previously taken this course, I had not completed the assignments as they were written in Octave. However, I recently discovered a repository that offered a Python version of the assignments, which motivated me to retake the course.
Coursera page:
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning (Assiginments unavailable)
This repo is originally forked from https://github.com/dibgerge/ml-coursera-python-assignments.
Please note that as of June 2022, the official assignments have been rewritten in Python and are now available exclusively through a paid subscription. To access the latest assignments, kindly refer to the official homepage and subscribe.
Note: The official assignments are updated and not free anymore, so the solutions are not submitted to the official grader.
- Exercise01. Linear regression
- Exercise02. Classification
- Exercise03. Multi-class Classification and Neural Networks
- Exercise04. Neural Networks Learning
- Exercise05. Regularized Linear Regression and Bias vs Variance
- Exercise06. Support Vector Machines (Feel free to skip this one, as it's not included in the 2022 edition)
- Exercise07. K-means Clustering and Principal Component Analysis
- Exercise08. Anomaly Detection and Recommender Systems
š¤ Welcome to check my repo cs-courses.
Join me and enjoy the journey š