Knowledge
  • My Knowledge Wiki
  • Courses
    • Courses
    • Coursera
      • Machine Learning
        • Week 1
          • Introduction
        • Week 2
          • Linear Regression with Multiple Variables
    • fast.ai
      • fast.ai
      • Deep Learning Part 1: Practical Deep Learning for Coders
        • Deep Learning Part 1: 2018 Edition (v2)
          • Lesson 1
        • Deep Learning Part 1: 2019 Edition (v3)
          • Lesson 1 - Image Recognition
          • Lesson 2 - Computer Vision: Deeper Applications
          • Lesson 3 - Multi-label, Segmentation, Image Regression, and More
          • Lesson 4 - NLP, Tabular, and Collaborative Filtering
          • Lesson 5 - Foundations of Neural Networks
          • Lesson 6 - Foundations of Convolutional Neural Networks
          • Lesson 7 - ResNets, U-Nets, GANs and RNNs
      • Deep Learning Part 2: Cutting Edge Deep Learning for Coders
        • Deep Learning Part 2: 2017 Edition (v1)
          • Lesson 8 - Artistic Style
          • Lesson 9 - Generative Models
          • Lesson 10 - Multi-modal & GANs
          • Lesson 11 - Memory Networks
          • Lesson 12 - Attentional Models
          • Lesson 13 - Neural Translation
          • Lesson 14 - Time Series & Segmentation
        • Deep Learning Part 2: 2018 Edition (v2)
          • Lesson 8 - Object Detection
          • Lesson 9 - Single Shot Multibox Detector (SSD)
          • Lesson 10 - Transfer Learning for NLP and NLP Classification
          • Lesson 11 - Neural Translation; Multi-modal Learning
          • Lesson 12 - DarkNet; Generative Adversarial Networks (GANs)
          • Lesson 13 - Image Enhancement; Style Transfer; Data Ethics
          • Lesson 14 - Super Resolution; Image Segmentation with U-Net
      • Machine Learning: Intro to Machine Learning for Coders
        • Machine Learning: 2017 Edition
          • Lesson 1 - Introduction to Random Forests
          • Lesson 2 - Random Forest Deep Dive
          • Lesson 3 - Feature Engineering
          • Lesson 4 - Random Forest Interpretation
          • Lesson 5 - Train vs Test
          • Lesson 6 - What is Machine Learning and Why Do We Use It
          • Lesson 7 - Decision Trees Ensemble
          • Lesson 8 - Basic Neural Networks
          • Lesson 9 - SGD; Neural Network Training; Broadcasting
          • Lesson 10 - Logistic Regression; NLP; Naive Bayes
          • Lesson 11 - Structured and Time-Series Data
          • Lesson 12 - Entity Embeddings; Data Science and Ethics
  • Books
    • Deep Work
  • Programming Languages
    • Programming Languages
      • JavaScript
        • JS Libraries
Powered by GitBook
On this page
  • My Knowledge Wiki
  • How to use the wiki effectively?
  • What kinds of contents
  • What kinds of notes
  • Other things I wrote and shared
  • Contributing
  • License

My Knowledge Wiki

NextCourses

Last updated 2 years ago

This wiki is now archived - look at if you would like an updated wiki. Thank you.

My Knowledge Wiki

Hey, this is a place where I document everything I know and learn so far about the world in the form of an online book. I am sharing them in the hope that they would be useful to you as well.

"An investment in knowledge pays the best interest."

— Ben Franklin

How to use the wiki effectively?

In the left corner, you can make searches for what content I have already indexed or you can simply explore the tree view to the left.

What kinds of contents

I want to remember more , so I take notes to share .

What kinds of notes

  • Notes on various computer science (technical) topics.

  • General notes.

  • Notes from projects that I've work on.

  • Notes from courses (educational materials) that I've study.

  • Notes from books and other interesting things that I've read.

Other things I wrote and shared

Contributing

License

I share my knowledge in a longer form by writing . I also love writing code and share it all on . You can find all the things I have made and shared thus far .

If you found a mistake anywhere in this wiki, I would really appreciate your help. You can quickly find any entry you wish to edit by and then making the changes.

Code: © Cedric Chee

Content:

wiki.cedricchee.com (InfoWarehouse)
of what I read
compressed wisdom
articles
GitHub
here
searching for the topic
MIT
Creative Commons Attribution 4.0 International License