DL basic

  • AI vs Machine Learning vs Deep Learning
  • History of Deep Learning
  • Types of Learning
    • Supervised
    • Unsupervised
    • Semi-supervised
    • Self-supervised
    • Reinforcement Learning 
  • Deep Learning Workflow
  • Applications
  • CPU vs GPU vs TPU
  • Popular Frameworks
    • TensorFlow
    • PyTorch

Neural Networks Basics

  • Biological Neuron
  • Artificial Neuron
  • Perceptron
  • Multi Layer Perceptron (MLP)
  • Feed Forward Neural Network
  • Hidden Layers
  • Forward Propagation
  • Backpropagation
  • Computational Graph
  • Loss Functions
    • MSE
    • MAE
    • BCE
    • CCE
    • Huber
  • Activation Functions
    • Linear
    • Sigmoid
    • Tanh
    • ReLU
    • Leaky ReLU
    • ELU
    • GELU
    • Softmax
  • Gradient Descent
    • Batch
    • SGD
    • Mini Batch
  • Optimizers
    • SGD
    • Momentum
    • Nesterov
    • AdaGrad
    • AdaDelta
    • RMSProp
    • Adam
    • AdamW
    • Nadam
    • Lion
  • Learning Rate
  • Learning Rate Scheduler
  • Warmup
  • Cosine Annealing
  • Gradient Clipping
  • Early Stopping

 Deep Neural Networks

  • Universal Approximation Theorem
  • Vanishing Gradient
  • Exploding Gradient
  • Weight Initialization
    • Xavier
    • He
  • Batch Normalization
  • Layer Normalization
  • Dropout
  • Regularization
    • L1
    • L2
    • Weight Decay
  • Residual Connections
  • Skip Connections
  • Mixed Precision Training
  • Checkpointing
  • Transfer Learning
  • Fine-Tuning
  • Residual Connections
  • Skip Connections
  • Early Stopping 

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


Computer Vision
  • OpenCV Basics
  • Image Processing
  • Thresholding
  • Edge Detection
  • Morphology
  • Contours
  • CNN Fundamentals
  • Convolution
  • Padding
  • Stride
  • Pooling
  • Data Augmentation
  • Transfer Learning
  • LeNet
  • AlexNet
  • VGG
  • GoogLeNet
  • ResNet
  • DenseNet
  • EfficientNet
  • MobileNet
  • ConvNeXt
  • Vision Transformer
  • Swin Transformer
  • Data Augmentation
  • Transfer Learning for Vision

Object Detection (need to discuss)

  • R-CNN
  • Fast R-CNN
  • Faster R-CNN
  • SSD
  • YOLO

Segmentation (need to discuss)

  • U-Net
  • Mask R-CNN
  • SAM
Application 
  • OCR
  • Face Recognition


NLP

  • Text Cleaning
  • Tokenization
  • Stemming
  • Lemmatization
  • Bag of Words
  • TF-IDF
  • N-Grams
  • Word2Vec
  • GloVe
  • FastText
  • Embeddings
  • RNN
  • LSTM
  • GRU
  • Seq2Seq
  • Attention Mechanism

Model Evaluation 

  • Train/Validation/Test Split
  • Confusion Matrix
  • Accuracy
  • Precision
  • Recall
  • F1 Score
  • ROC-AUC
  • PR Curve
  • Regression Metrics
  • Cross Validation
  • Hyperparameter Tuning
  • Grid Search
  • Random Search
  • Bayesian Optimization
  • Optuna
  • Bias-Variance
  • Underfitting
  • Overfitting
  • Learning Curves
  • SHAP
  • LIME
  • Train/Validation/Test Split
  • Precision-Recall Curve 

9. Transformers & LLMs

  • Transformer Architecture
  • Self Attention
  • Multi Head Attention
  • Positional Encoding
  • Encoder
  • Decoder
  • Tokenizers
  • Embeddings
  • BERT
  • GPT
  • T5
  • LLaMA
  • Mistral


Generative Deep Learning

Autoencoders

  • Vanilla
  • Sparse
  • Denoising
  • Variational Autoencoder (VAE)

GANs

  • DCGAN
  • Conditional GAN
  • Pix2Pix
  • CycleGAN
  • StyleGAN
  • StyleGAN2
  • ESRGAN

Diffusion Models

  • DDPM
  • Latent Diffusion
  • Stable Diffusion
  • ControlNet

Foundation Models

  • DALL·E
  • Midjourney
  • Imagen
  • FLUX
  • CLIP
  • BLIP
  • Vision Language Models (VLMs)
 Specialized Deep Learning
  • Graph Neural Networks (GNN)
  • Reinforcement Learning
    • DQN
    • PPO
  • Time Series Forecasting
  • Speech Recognition
  • Recommendation Systems
  • Multimodal AI
  • Multimodal AI

Responsible AI

  • Explainable AI (XAI)
  • Fairness
  • Bias
  • Privacy
  • Security
  • Ethics
  • AI Safety
  • Model Governance