This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments

This repository store my lecture notes-and-home work solutions for cs229 machine learning course standford

This repository contains course codes and slides for Coursera Machine Learning Specialisation Taught by Andrew NG(DeepLearning.AI) in collaboration with Standford University.

Machine learning problem sets from Stanford University's Machine Learning course on Coursera

Lecture slides and course materials for Standford's CS 329S: Machine Learning Systems Design

Standford "Machine Learning" course by Andrew Ng

Machine Learning from Andrew Ng at coursera.org with Standford

Programming assignments for Machine Learning by Standford University

Classic Machine Learning material from Andrew Ng. Matlab and Octave codes for assignments and optional exercises.

Updated Solutions and Implementations for Standford's CS229 Machine Learning

Solution to Andrew Ng's Machine Learning at Coursera.

Machine Learning is a wide range field, which mainly includes the following four parts: Supervised Learning, Unsupervised Learning, Weakly Supervised Learning and Reinforcement Learning. Also, deep learning is a sub-field of machine learning. Knowing what machine learning includes, understanding the mathematical principles and implementation details of these contents, and learning the specific ideas behind them are far more important than just calling python libraries to solve certain tasks. I have been playing machine learning for more than 2 years, including taking various machine learning-related courses and completing machine learning-related tasks. These courses include: Standford MachineLearning course , Coursera DeepLearning course taught by Andrew Ng; SJTU CS420 Machine Learning course and CS410 Artificial Intelligence course; CSDN machine learning course taught by Shunxiang Liu. The machine learning-related books I have read include: Professor Zhou Zhihua’s "machine learning book" (watermelon book), Ian Goodfellow's "Deep Learning" book (flower book) and Francois Chollet's "Deep Learning with Python". They are all very helpful to me. The machine learning related projects (codes and their corresponding description, reports) are also included in this repository. In short, this repository contains a lot of content, and I hope it can be helpful to you.

Notes on Octave commands shared on Machine Learning Coursera course - Standford University

Machine Learning Standford Course by Andrew Ng

Programming Exercise code from the "Standford Machine Learning" class on Coursera.org.

This is a repository of my Coursera Machine Learning - Standford guided by Andrew NG with course assignments, lecture and quizzes

Coursera Andrew Ng's Machine Learning Course.

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Coursera Machine Learning class from Andrew Ng

Here we will look into the labs and code in stanford machine learning course

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The matlab code in learning machine learning.

This repository will hold all my code submissions for assignments for the coursera course: Machine Learning by Andrew Ng. Course Link: https://www.coursera.org/learn/machine-learning

Coursera Machine Learning Standford

Machine Learning by standford university

Strongly recommanded machine learning courses from Standford University for medium level learner , with note and answers. Period: 3 month

Machine Learning Course at Standford

Coursera - Machine Learning - Standford University