Machine Learning Online Courses

The following is the content of this page

• Description
• Content
• Detail

Description

• The following is a list of online courses about machine learning. (enrolled, completed, interested)
• The order does not matter
• The list is created on my own experience
• I will keep updating this repo.

Content

• Stanford Machine Learning | Coursera
• UW Machine Learning | Coursera
  • Machine Learning Foundations: A Case Study Approach | Coursera
  • Machine Learning: Regression | Coursera
  • Machine Learning: Classification | Coursera
  • Machine Learning: Clustering & Retrieval | Coursera
• Stanford CS229 Machine Learning
• Stanford Algorithms | Coursera
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms | Coursera
  • Graph Search, Shortest Paths, and Data Structures | Coursera
  • Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming | Coursera
• UIUC Data Mining | Coursera
  • Data Visualization | Coursera
  • Text Retrieval and Search Engines | Coursera
• Ng Deep Learning | Coursera
  • Neural Networks and Deep Learning | Coursera
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Coursera
  • Structuring Machine Learning Projects | Coursera
  • Convolutional Neural Networks | Coursera
• Stanford CS231n: Convolutional Neural Networks for Visual Recognition
• Rice Fundamentals of Computing | Coursera
  • An Introduction to Interactive Programming in Python (Part 1) | Coursera
  • An Introduction to Interactive Programming in Python (Part 2) | Coursera
  • Principles of Computing (Part 1) | Coursera
• Peking 程序设计与算法 | Coursera
  • 计算导论与C语言基础 | Coursera
  • C程序设计进阶 | Coursera
• HSE Advanced Machine Learning Specialization | Coursera
  • Introduction to Deep Learning | Coursera
• Machine Learning Engineer Nanodegree | Udacity
• Deep learning | Udacity
• How to Use Git and GitHub | Udacity
• Intro to Computer Science | Udacity
• Programming Foundations with Python | Udacity

Detail

1. Stanford Machine Learning | Coursera

• Recommend, fundamental concepts

• Time consuming: two weeks, or one week in hard-working

• Schedule: Completed

• Note: None

• I want to say: This is my first course in machine learning.

2. University of Washington Machine Learning | Coursera

• Courses:

  1. Machine Learning Foundations: A Case Study Approach | Coursera
  2. Machine Learning: Regression | Coursera
  3. Machine Learning: Classification | Coursera
  4. Machine Learning: Clustering & Retrieval | Coursera

• Highly Recommend, machine learning algorithms

• Time consuming: one day per week, from 9:00am to 24:00pm, I'm using pandas partially, it could be faster for sframe.

• Schedule: 4/4, Completed

• Note: None

• I want to say:

  • This course teach you how to build a model from scratch and how to use it.
  • Programming assignments are very time consuming.

3. Stanford CS229 Machine Learning

• Recommend, machine learning algorithms

• Time consuming: Very slow for personal reason.

• Schedule: Interested

• Note: None

• I want to say: None

4. Stanford Algorithms | Coursera

• Courses:

  1. Divide and Conquer, Sorting and Searching, and Randomized Algorithms | Coursera
  2. Graph Search, Shortest Paths, and Data Structures | Coursera
  3. Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming | Coursera

• Recommend, computer science algorithms

• Time consuming: one day per week, from 9:00am to 24:00pm

• Schedule: 3/4 Completed

• Note: None

• I want to say:

  • I have completed the first three courses. Many programming assignments need more optimization.
  • Programming assignments are very time consuming.
  • Learn how to think as a computer scientist.

5. UIUC Data Mining | Coursera

• Courses:

  1. Data Visualization | Coursera
  2. Text Retrieval and Search Engines | Coursera

• Recommend, data mining

• Time consuming: one day per week, from 9:00am to 24:00pm

• Schedule: 2/6 Completed

• Note: None

• I want to say:

  • I have completed the only first two courses for two reasons. Time consuming and problems about programming assignments.
  • The first course is helpful to those want to be a data analysis.
  • The second course introduce the fundamental concepts and application.

6. Ng Deep Learning | Coursera

• Courses:

  1. Neural Networks and Deep Learning | Coursera
  2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Coursera
  3. Structuring Machine Learning Projects | Coursera
  4. Convolutional Neural Networks | Coursera

• Highly Recommend, deep learning

• Time consuming: one day or a half per week

• Schedule: 4/5

• Note: None

• I want to say: I'm taking. I love this specialization

7. Stanford CS231n: Convolutional Neural Networks for Visual Recognition

• Recommend, deep learning

• Time consuming: Very slow for personal reason.

• Schedule: interested

• Note: None

• I want to say: I only complete the CNN part of this course

8. Rice University Fundamentals of Computing | Coursera

• Courses:

  1. An Introduction to Interactive Programming in Python (Part 1) | Coursera
  2. An Introduction to Interactive Programming in Python (Part 2) | Coursera
  3. Principles of Computing (Part 1) | Coursera

• Recommend, I want to proficient in Python

• Time consuming: one evening or two

• Schedule: 3/7

• Note: None

• I want to say: I'm taking. Very interesting tiny games. Making progress for proficient in Python

9. Peking University 程序设计与算法 | Coursera

• Courses:

  1. 计算导论与C语言基础 | Coursera
  2. C程序设计进阶 | Coursera

• Recommend, I want to proficient in C/C++

• Time consuming: two evenings

• Schedule: 2/7

• Note: None

• I want to say: I'm taking. Making progress for familiar with C/C++

10. HSE Advanced Machine Learning Specialization | Coursera

• Courses:

  1. Introduction to Deep Learning | Coursera

• Recommend, machine learning algorithms

• Time consuming: one day per week

• Schedule: 1/6

• Note: None

• I want to say: I'm taking

11. Machine Learning Engineer Nanodegree | Udacity

• Courses:

• Recommend,

• Time consuming: one month

• Schedule: Capstone

• Note: None

• I want to say:

  • Add projects in your resume.
  • Teach you the application of machine learning.
  • Consisting of supervised learning, unsupervised learning, reinforcement learning and deep learning.
  • It is not too difficult to complete the projects, but plenty of skills need to know.

12. Deep learning | Udacity

• Not Recommend for fresh machine learning, deep learning

• Time consuming:

• Schedule: Completed

• Note: None

• I want to say:

  • It is a little difficult for those fresh machine learners.
  • Not as good as deep learning part of machine learning nano degree

13. How to Use Git and GitHub | Udacity

• Recommend, Git and Github

• Time consuming: eithor one day or three days, I forget

• Schedule: Completed

• Note: None

• I want to say: Good course for me, but I do not use all the skills learned from this coures.

14. Intro to Computer Science | Udacity

• Recommend, I want to know more about Python

• Time consuming: Very long, 2 months

• Schedule: Completed

• Note:

  • Course's description, content, question and answer in Udacity can be found in my blog

• I want to say:

  • time consuming
  • Introduction to computer science via python and web crawling
  • I wrote a script to crawl the content of Udacity to write my blog after this course

15. Programming Foundations with Python | Udacity

• Highly Recommend, short introduction to python

• Time consuming: one day or two days

• Schedule: Completed

• Note: None

• I want to say:

  • Good course for fresh programmers.
  • You would know function, how to use class, how to build class after this course