https://github.com/nsoojin/coursera-ml-py-sj

https://github.com/nsoojin/coursera-ml-py-sj

andrew-ng-course andrew-ng-machine-learning andrew-ng-ml-course anomaly-detection coursera-machine-learning kmeans-clustering logistic-regression machine-learning-exercises neural-network numpy-exercises support-vector-machine

Last synced: about 1 month ago
JSON representation

• Host: GitHub
• URL: https://github.com/nsoojin/coursera-ml-py-sj
• Owner: nsoojin
• Created: 2017-03-23T01:06:52.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-03-24T05:28:19.000Z (about 8 years ago)
• Last Synced: 2025-04-22T06:52:58.823Z (about 1 month ago)
• Topics: andrew-ng-course, andrew-ng-machine-learning, andrew-ng-ml-course, anomaly-detection, coursera-machine-learning, kmeans-clustering, logistic-regression, machine-learning-exercises, neural-network, numpy-exercises, support-vector-machine
• Language: Python
• Size: 18.3 MB
• Stars: 41
• Watchers: 2
• Forks: 20
• Open Issues: 1
• Metadata Files:
  • Readme: readme.md

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README

        
# Coursera Machine Learning Assignments in Python

[![author](https://img.shields.io/badge/author-nsoojin-red.svg)](https://www.linkedin.com/in/soojinro) [![python](https://img.shields.io/badge/python-3.6-blue.svg)]() [![license](https://img.shields.io/github/license/mashape/apistatus.svg)]() [![contribution](https://img.shields.io/badge/contribution-welcome-brightgreen.svg)]()

## About

If you've finished the amazing introductory Machine Learning on Coursera by Prof. Andrew Ng, you probably got familiar with Octave/Matlab programming. With this repo, you can re-implement them in Python, step-by-step, visually checking your work along the way, just as the course assignments.

## How to start

This repository is my implementation of the assignments. You can do your own by cloning this [repo](https://github.com/nsoojin/coursera-ml-py).