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DL Basic

  • Roadmap
  • History of DL
  • AI vs ML vs DL vs GenAI
  • Types of Learning
  • Deep Learning Workflow
  • Applications of Deep Learning
  • CPU vs GPU vs TPU
  • Popular Frameworks

Neural Networks

  • Biological Neuron
  • Perceptron
  • Multi Layer Perceptron (MLP)
  • Feed Forward Neural Network
  • Hidden Layers
  • Forward Propagation
  • Backpropagation
  • Computational Graph
  • Loss Functions
  • Activation Functions
  • Gradient Descent
  • Learning Rate
  • Learning Rate Scheduler
  • Warmup
  • Cosine Annealing
  • Gradient Clipping
  • Early Stopping

Deep Neural Networks

  • Universal Approximation Theorem
  • Vanishing Gradient
  • Exploding Gradient
  • Weight Initialization
  • Regularization in DL
  • Introduction to TensorFlow
  • Introduction to PyTorch
  • Building first neural network
  • Training custom models
  • Batch Normalization
  • Layer Normalization
  • Dropout
  • Regularization
  • Residual Connections
  • Skip Connections
  • Mixed Precision Training
  • Checkpointing
  • Transfer Learning
  • Fine-Tuning

TensorFlow & Keras

  • Installation
  • Tensors
  • Tensor Operations
  • Keras
  • Sequential API
  • Functional API
  • Model Subclassing
  • Custom Layers
  • Custom Loss
  • Custom Metrics
  • Custom Training Loop
  • TensorBoard
  • Save/Load Models
  • Model Deployment Basics

PyTorch

  • Installation
  • Tensors
  • Autograd
  • Dataset
  • DataLoader
  • nn.Module
  • Optimizers
  • Training Loop
  • Validation
  • Callbacks
  • TorchScript
  • ONNX Export
  • Save/Load Models

Deep Learning Tutorial

Learn Deep Learning with our comprehensive tutorials

DL Basic

8 topics →

Neural Networks

17 topics →

Deep Neural Networks

19 topics →

TensorFlow & Keras

14 topics →

PyTorch

13 topics →

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