ssundar6087 / deep-learning

Machine Learning Resources / Learning Plan

Foundations

Linear Algebra

• Computational Linear Algebra for Coders: https://github.com/fastai/numerical-linear-algebra/blob/master/README.md
• Gilbert Strang's Linear Algebra and Learning from Data book: https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/video-lectures/

Calculus

• Multivariate Calculus: https://www.coursera.org/learn/multivariate-calculus-machine-learning

Generic Machine Learning

• Andrew Ng's ML Course: https://www.coursera.org/learn/machine-learning
• FastAI's ML Course: http://course18.fast.ai/ml
• Google's ML Crash Course: https://developers.google.com/machine-learning/crash-course/

Deep Learning First Principles

• Deep Learning AI Specialization: https://www.coursera.org/specializations/deep-learning
• FastAI Part I: https://course.fast.ai/
• FastAI Part II: http://course18.fast.ai/part2.html
• Full Stack DL: https://fullstackdeeplearning.com/march2019

Computer Vision

• Stanford's CS 231n:
  • Course Home Page: http://cs231n.github.io/
  • Playlist: https://www.youtube.com/playlist?list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk

Natural Language Processing

• Stanford's CS 224n:
  • Course Home Page: http://web.stanford.edu/class/cs224n/
  • Playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z

Audio

• FastAI Lectures (when available)

Frameworks

Tensorflow

• Coursera TF Specialization:
  • Introduction to Tensorflow: https://www.coursera.org/learn/introduction-tensorflow
  • CNN's in Tensorflow: https://www.coursera.org/learn/convolutional-neural-networks-tensorflow
• FastAI's Swift for TF lessons:
  • Learn Swift:
  • Create a small library based on swift for TF for Computer Vision
• Deep Dive into Tensorflow Internals: https://www.youtube.com/watch?v=kVEOCfBy9uY&list=PLOJ0FSJhiKlw9ZokOzxOOnxK6PQuU7YIx

Pytorch

• Official Pytorch tutorial: https://pytorch.org/tutorials/
• Introduction to Deep learning with Pytorch: https://www.udacity.com/course/deep-learning-pytorch--ud188

Projects

Kaggle

• To add competitions and code to this list

Personal

• Build/Replicate a deep learning library from scratch using FastAI v3 Part II lessons
• Add SOTA methods and algorithms
• Use the library for competing in Kaggle and other contests

Papers

• Useful papers to be referenced here with sample code if possible