Open source to learn

Computational Thinking 101

• Source
  1. Kelas terbuka
  2. Microsoft Research
  3. Bukalapak

Basic Math,Probability and etc

Online Course

• Khanacademy (English version) link
• kind of Probabilistic from Prof. Knudson link
• MIT math and linear algebra link
• Foundations of Machine Learning link
• Additional resource :
  1. Statquest
  2. 3Blue1Brown (Math in general)
  3. Steve Brunton (Machine Learning for control theory and dynamical system)
  4. Deep Lizard (Deep learning)

Summary open Books

• Data Mining and Machine Learning: Fundamental Concepts and Algorithms Link

  Note: this book provides basic knowledge of data mining, the first part (data analysis basics) introduces the basics for understanding the book. The best part of this book is that, for each chapter (especially after the first part) it always gives a fundamental view of the chapter whether mathematical, probabilistic, etc.

• Mathematics for Machine Learning Link Online course : 1.coursera 2.youtube linear algebra, Multivariate Calculus

• Kevin Patrick Murphy open books (part I):

  1. Probabilistic Machine Learning: Advanced Topics link

  2. Probabilistic Machine Learning: An Introduction link

Specific open books

• Introduction to probability, statistics, and random processes link

• Probability and Statistics - The Science of Uncertainty, Second Edition link

• Linear Algebra link, video

All about Python

• MIT COURSE :
  1. Introduction to Computer Science and Programming in Python youtube, lecture source
  2. Introduction to Computational Thinking and Data Science youtube, lecture source

• Books: Python Programming And Numerical Methods: A Guide For Engineers And Scientists link

• Books : Python Data Science Handbook link

• Cognitive Class
  1. Python for datascience
  2. Data Analyst With python
  3. Data Visualization With Python
• Jetbrain Academy link
  • NOTE: Jetbrain Academy/Hyperskill, is a course that leads you to learn by doing. unfortunately, this course is limited to certain times. first of all, you have to choose a project that gives you credits to study in 1 month and if you complete it, JetBrains will give you extra credits to learn more.
• Additional Resource: Programiz,Real Python

Machine Learning,Deep Learning things

Course

• Deep learning (Andrew ng from standford) link

• 101 Deep learnig MIT link

• Standford
  1. Machine learning with graph link, cource
  2. NLP with Deep Learning link
  3. Introduction to Deep Learning for Computer Vision link
  4. Mining Massive Data Sets link
• TUM
  1. Introduction to Deep learning link
  2. Computer vision playlist link
• Soul National University
  1. Machine Learning for Visual Understandinglink

Books

• An Introduction to Statistical Learning link

• Deep Learning link

• Understanding Machine Learning: From Theory to Algorithms link

• Kevin Patrick Murphy open books (after part I)

• Dive To Deep learning link

• Foundations of Machine Learning link

• Pattern Recognition and Machine Learning link

Unopen book

• Neural Networks and Deep Learning: A Textbook link (Recommended)

• Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition link (Recommended)

Deep learning Frame Work

Course

• Microsoft open course :
  1. Pytorch link
  2. Tensorflow link
• Tensorflow official website link
• Pytorch Official Website link
• https://uvadlc-notebooks.readthedocs.io/en/latest/index.html
• full stack deep learning link

Open book

TBD