How to learn machine learning as a complete beginner: a self-study guide

A step-by-step roadmap of how to learn machine learning as a beginner.

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BOOK RECOMMENDATIONS

Grokking Deep Learning by Andrew Trask

The 100-page Machine Learning Handbook by Andriy Burkov

Deep Learning with PyTorch by Laura Mitchell, Sri Yogesh K, and Vishnu Subramanian

1a. FEED-FORWARD NEURAL NETWORKS

Chapter 1 of Book by Michael Nielsen: https://neuralnetworksanddeeplearning...

Grokking Deep Learning (Chapters 2,3)

The 100-page Machine Learning Handbook (Chapter 3.1, 3.2, Chapter 6)

1b. GRADIENT DESCENT / BACKPROPAGATION

Grokking Deep Learning (Chapters 4,6)

Chapter 2 of Book by Michael Nielsen:
https://neuralnetworksanddeeplearning...

2. CONVOLUTIONAL NEURAL NETWORKS

Two videos by Computerphile:
Blurs and filters:    • How Blurs & Filters Work - Computerphile  

Edge detection:    • Finding the Edges (Sobel Operator) - ...  

Intro to CNNs:    • CNN: Convolutional Neural Networks Ex...  

Deep Learning with PyTorch (Chapter 5)

3. RECURRENT NEURAL NETWORKS

Grokking Deep Learning (Chapters 11 and 12)

Video by Serrano Academy:    • A friendly introduction to Recurrent ...  

Stat Quest:    • Recurrent Neural Networks (RNNs), Cle...  

4. AUTOENCODERS

Deep Learning with Pytorch (Chapter 6).

Video playlist by Digital Sreeni:
   • Autoencoders and their applications  

5. REINFORCEMENT LEARNING

Deep Learning with Pytorch (Chapter 9).

6. ATTENTION

Blog post by Jay Alammar: https://jalammar.github.io/illustrate...

Lecture by Stanford Online:    • Stanford CS25: V2 I Introduction to T...  

Intro: (0:00)
Three book recommendations: (0:53)
Feed-Forward Neural Networks: (2:06)
Convolutional Neural Networks: (4:12)
Recurrent Neural Networks: (5:21)
Autoencoders: (6:36)
Reinforcement Learning: (7:20)
Attention: (7:54)
General Tips: (9:06)