Byte by Byte Vision

Welcome to Byte-by-Byte Vision, your go-to platform for high-quality, curated resources in deep learning and computer vision. Learn at your own pace with structured paths, whether you’re a beginner or refining your expertise. Dive in and explore the transformative world of CV!
Author

Soumyaratna Debnath

Published

July 1, 2024

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  1. ML Was Hard Until I Learned These 5 Secrets!
  2. How I’d learn ML (if I could start over)
  3. Neural Networks Implemented From Scratch
  4. DeepLearning - Mitesh Khapra
  5. Neural Networks by 3-Blue-1-Brown
  6. Understanding Deep Learning by Simon J.D. Prince Book and YouTube Playlist

Mathematics

  1. Basic probability: Joint, marginal and conditional probability | Independence
  2. What is Prior And Posterior
  3. Mathematics for Deep Learning Playlist
  4. Mathematics for Deep Learning with Codes

Articles

  1. Vector Calculus - Michael Corra
  2. Quantum Computing for the Quantum Curious - Ciaran Hughes
  3. The Map of Quantum Computing

PyTorch and Visualizations

  1. PyTorch Tutorials - Complete Beginner Course
  2. PyTorch Lightning Tutorial
  3. Complete TensorBoard Guide

Graph Neural Networks

  1. Graph Neural Networks - DeepFindr
  2. Graph Convolutional Networks using only NumPy
  3. Find the related codes here

Vision Transformers

  1. Attention in transformers, visually explained
  2. The Illustrated Transformer
  3. Transformer Neural Networks Derived from Scratch
  4. Vision Transformer from Scratch
  5. Implement and Train ViT From Scratch for Image Recognition - PyTorch
  6. Vision Transformer in PyTorch
  7. Find the related codes here

Generative Adversarial Networks

  1. Understand the Math and Theory of GANs
  2. Building our first simple GAN
  3. Pix2Pix Paper Walkthrough and implementation from scratch
  4. CycleGAN Paper Walkthrough and implementation from scratch
  5. ProGAN Paper Walkthrough and implementation from scratch
  6. SRGAN Paper Walkthrough and implementation from scratch
  7. StyleGAN Paper Walkthorugh and implementation from scratch
  8. Find the related codes here

Variational Autoencoder

  1. Variational Autoencoder Explained
  2. Variational AutoEncoder Paper Walkthrough and implementation from scratch
  3. Find the related codes here

Diffusion Models

  1. Diffusion models explained in 4-difficulty levels
  2. What are Diffusion Models?
  3. Diffusion Models | Paper Explanation | Math Explained
  4. Diffusion Models - Live Coding Tutorial
  5. DDPM Explained and implementation from scratch
  6. What is Stable Diffusion?
  7. Coding Stable Diffusion from scratch in PyTorch

Neural Radiance Field (NeRF)

  1. Neural Radiance Fields Paper Explained
  2. How NeRF and Instant Neural Graphics Primitives Work
  3. Understanding NeRFs
  4. Coding Neural Radiance Fields
  5. Nerf Code Explained

3D Gaussian Splatting

  1. 3D Gaussian Splatting - Explained!
  2. Computer Science Maths Cheat Sheet
  3. 3D Gaussian Splatting
  4. Gaussian Splatting Explorations

Additional References

  1. Tom Yeh | AI by Hand
  2. AI But Simple
  3. Understand Convolution : Better Explined, Mathworks
  4. Explained Visually

Interview PrepMat

  1. What is RNN and LSTM?
  2. RNN, LSTM and GRU explained.
  3. YOLOv1 Explained

Data Structures and Algorithms

  1. Algorithms | Abdul Bari
  2. Algorithms Handwritten Notes
  3. Dynamic Programming Playlist