Deep Learning Roadmap for Beginners to AdvancedLast updated: Apr 3, 2026Author :Jitendra KumarLinear Algebra for DL (Vectors, Matrices, Tensors)Calculus (Derivatives, Chain Rule, Partial Derivatives)Understanding Loss FunctionsFoundationsProbability & Statistics for DLOptimization Basics (Gradient Descent, Learning Rate)PerceptronsActivation Functions (ReLU, Sigmoid, Tanh, Softmax)Training, Validation, TestingNeural Networks BasicsFeedforward Neural NetworksForward & BackpropagationRegularization (L1, L2, Dropout, BatchNorm)Stochastic Gradient Descent (SGD)Weight Initialization TechniquesVanishing & Exploding Gradient ProblemOptimization & Training TechniquesMomentum, RMSProp, Adam, AdamWLearning Rate SchedulersConvolutional Neural Networks (CNNs)Long Short-Term Memory (LSTMs)Attention MechanismGraph Neural Networks (GNNs)Generative Adversarial Networks (GANs)Deep ArchitecturesRecurrent Neural Networks (RNNs)Gated Recurrent Units (GRUs)TransformersAutoencoders & Variational AutoencodersData Preprocessing & AugmentationBuilding DL Models with TensorFlowHyperparameter TuningPractical Deep LearningTransfer Learning & Fine-TuningBuilding DL Models with PyTorchExperiment Tracking (TensorBoard, MLflow)Computer Vision (Image Classification, Object Detection, Segmentation)Speech Recognition & Audio ProcessingReinforcement Learning with Deep Q-NetworksSpecialized DomainsNatural Language Processing (Embeddings, Transformers, BERT, GPT)Time Series Forecasting with DLModel Compression (Pruning, Quantization, Distillation)Serving Models with Flask/FastAPIDockerizing Deep Learning ModelsScaling & DeploymentDistributed Training (Data Parallelism, Model Parallelism)Deploying with TensorFlow Serving & TorchServeEdge & Mobile Deployment (TensorFlow Lite, ONNX)Self-Supervised LearningLarge Language Models (LLMs)Federated LearningAdvanced TopicsFew-Shot & Zero-Shot LearningDiffusion Models (Stable Diffusion, DALL·E)Ethics & Bias in Deep LearningImage Classification (CIFAR-10, MNIST)Text Sentiment AnalysisMusic or Image Generation with GANsProjectsObject Detection (YOLO, Faster R-CNN)Machine Translation (Seq2Seq with Attention)Fine-tuning BERT or GPT on Custom DatasetNeural Network Fundamentals Q&AOptimization & Training QuestionsSystem Design for Deep Learning ModelsInterview PreparationCNNs, RNNs & Transformers Q&ACase Studies (Image Search, Chatbots, Recommendation)
