Deep Learning

1Index 2DL Intro 3Neural Network Basics 4Activation Functions 5Forward Propagation 6Backpropagation 7Loss Functions 8Optimizers 9PyTorch Fundamentals 10TF Keras Basics 11Data Loading 12Training Loop 13Regularization 14Hyperparameter Tuning 15Weight Initialization 16CNN Intro 17Convolution Deep Dive 18Famous CNN Architectures 19Transfer Learning 20Image Classification 21Object Detection 22Image Segmentation 23CNN Visualization 24CNN Best Practices 25RNN Intro 26LSTM Deep Dive 27GRU Variants 28Sequence Modeling 29Attention Mechanism 30Word Embeddings 31Text Classification 32Named Entity Recognition 33Transformer Architecture 34BERT Deep Dive 35GPT Language Models 36Vision Transformers 37Transformer Variants 38Pre training Strategies 39Fine tuning Techniques 40Prompt Engineering DL 41Efficient Transformers 42Autoencoders 43Variational Autoencoder 44GAN Fundamentals 45GAN Variants 46Diffusion Models 47Neural Style Transfer 48Image Super Resolution 49Image Inpainting 50Graph Neural Networks 51Vision Transformers 52Multimodal Models 53NAS 54Self Supervised 55Few Shot Learning 56Mixture of Experts 57Word Embeddings 58Text Classification 59NER 60Machine Translation 61Question Answering 62Summarization 63Advanced Object Detection 643D Vision 65Video Understanding 66OCR Document AI 67Medical Imaging 68CV Projects 69Model Compression 70Quantization 71ONNX Export 72Edge Deployment 73GPU Distributed 74AI Safety Ethics 75Reading Papers 76DL Career Guide