Concepts

• Basics
  • Deep Learning - Concepts - Basics
  • Table of Content
  • Neural Network
  • Activation Function
  • The PERCEPTRION ERROR
  • Gradient in Neural Network
  • Vanishing/Exploding Gradient
  • Weights Initialization In NN
  • Regularization
  • Normalization
  • Parameters Initialization
  • Gradient Checking
  • Optimizers
  • Hyper-Parameters Tuning
  • Batch Normalization
  • Multi-Class Classification
  • BIAS - Variance
  • Single Number Evaluation Metric
  • Avoidable Bias
  • Error Analysis
  • Mismatched Training & Dev/Test Sets
  • Learning From Multiple Tasks
  • End-To-End Deep Learning
  • Credits
• Convolution
  • Deep Learning - Concepts - Convolution
  • Abstract
  • What made the jump to use deep learning in computer vision field?
  • Motivation to Introduce Conveolution Concept
  • Convolution
  • Filter/Kernel
  • Padding
  • Strided Convolution
  • Volume Convolution
  • Pooling Layer
  • CNN Example
  • Why Convolution
  • Transponsed Convolution
  • Multiple Input
  • Case Studies: Classic Networks
  • Comparison between Classic Networks
  • Case Studies: Residual Neural Networks
  • Case Studies: Inception Networks
  • Case Studies: Mobile Net
  • Practical Advices using ConvNet
  • Detection Algorithms
  • Detection Algorithms - YOLO Algorithm
  • YOLOv3 Architecture [Optional]
  • Detection Algorithms - Semantic Segmentation
  • Face Recognition
  • Neural Style Transfer
  • State-of-Art
  • Credits
• Historyofai
  • Deep Learning - Concepts - History of AI
• Sequencemodels
  • Deep Learning - Concepts - Sequence Models
  • Table of Content
  • History of Large Language Model
  • Examples of Sequence Data
  • Different between NLP and LLM
• Stateofart
  • Deep Learning - Concepts - State of Art
  • Table of Content
  • Abstract
  • Architecture Vs Model
  • Id Face Extraction