AI, But Simple

Archive 124 issues

CategoryAll

2025 51

  1. #44 Diffusion Transformers (DiTs), Simply Explained Architecture PRO edition
  2. #43 A Simple Guide To RNNs Architecture PRO edition
  3. #42 Recommender Systems, Simply Explained Foundation PRO edition
  4. #41 CNN Backpropagation, Mathematically Explained Training PRO edition
  5. #40 Language Models Are Few-Shot Learners: The Introduction of GPT-3 LLMs PRO edition
  6. #39 Deep Learning's Top Pitfalls: Why Your Model Struggles (And How to Fix It!) Training PRO edition
  7. #38 Transformers and Self-Attention, Mathematically Explained Architecture PRO edition
  8. #37 Transformers and Multi-Head Attention, Mathematically Explained Architecture PRO edition
  9. #36 Neural Architecture Search (NAS) Architecture PRO edition
  10. #35 Self-Supervised Learning, Simply Explained Training PRO edition
  11. #34 Convolutional Neural Networks (CNNs) In Pytorch Architecture PRO edition
  12. #33 Logistic Regression, Mathematically Explained Foundation PRO edition

2024 32

  1. #32 Vision Transformers (ViTs) Architecture PRO edition
  2. #31 Generative Adversarial Networks, Simplified Architecture PRO edition
  3. #30 Transfer Learning, Simplified Training PRO edition
  4. #29 Normalization In Deep Learning Training PRO edition
  5. #28 All About Activation Functions Training PRO edition
  6. #27 Introduction to Deep Learning Foundation PRO edition
  7. #26 Linear Regression, Mathematically Explained Foundation PRO edition
  8. #25 Efficient Optimization Algorithms: Mathematically Explained Training PRO edition
  9. #24 Optimization Algorithms in Deep Learning: Mathematically Explained Training PRO edition
  10. #23 Mathematics of Recurrent Neural Networks: Backpropagation Training PRO edition
  11. #22 Recurrent Neural Networks, Explained Mathematically Architecture PRO edition
  12. #21 Deep Learning Common Terms and Misconceptions Foundation PRO edition
  13. #20 Convolutional Neural Networks, Explained Mathematically Architecture PRO edition
  14. #19 Transformers and the Attention Mechanism Architecture PRO edition
  15. #18 MLP Learning Process: The Math Behind Deep Learning Foundation
  16. #17 Multilayer Perceptrons: The Math Behind Deep Learning Foundation
  17. #16 Deep Unsupervised Learning: Autoencoders Foundation
  18. #15 Recurrent Neural Networks, Revisited Architecture
  19. #14 Modern Convolutional Neural Network Architectures Architecture
  20. #13 Unsupervised Machine Learning: Clustering Foundation
  21. #12 Batch Normalization Training
  22. #11 Neural Networks in Pytorch Foundation
  23. #10 Supervised Machine Learning, Simplified Foundation
  24. #9 Fundamentals of Reinforcement Learning RL
  25. #8 Recurrent Neural Networks, Simplified Architecture
  26. #7 Regularization in Deep Learning Training
  27. #6 Hyperparameter Tuning for Deep Learning Training
  28. #5 Optimizers in Deep Learning: A simple explanation Training