Deep Learning Tutorial
Deep Learning is one of the most important technologies in the modern world.
What You Will Learn
- Learn the basics of Deep Learning
- Understand core concepts and syntax
- Build practical projects
- Best practices and modern techniques
Course Content
INTRODUCTION TO DEEP LEARNING
Chapter 1
β
NEURAL NETWORK
Chapter 2
β
FUNDAMENTALS OF TRAINING
Chapter 3
β
IMPORTANT ACTIVATION FUNCTIONS
Chapter 4
β
ESSENTIAL PYTHON & LIBRARIES
Chapter 5
β
BUILDING YOUR FIRST NEURAL NETWORKS
Chapter 6
β
EXERCISES WITH PYTHON CODE
Chapter 7
β
CONVOLUTIONAL NEURAL NETWORKS (CNNs)
Chapter 8
β
RECURRENT NEURAL NETWORKS (RNNs)
Chapter 9
β
OPTIMIZATION TECHNIQUES
Chapter 10
β
DATA PREPROCESSING & AUGMENTATION
Chapter 11
β
AUTOENCODERS
Chapter 12
β
TRANSFER LEARNING
Chapter 13
β
SEQUENCE MODELS FOR NLP
Chapter 14
β
DEPLOYMENT BASICS
Chapter 15
β
TRANSFORMERS
Chapter 16
β
GENERATIVE MODELS
Chapter 17
β
REINFORCEMENT LEARNING
Chapter 18
β
GRAPH NEURAL NETWORKS (GNNs)
Chapter 19
β
ADVANCED CNN
Chapter 20
β
ADVANCED NLP
Chapter 21
β
TRANSFORMERS IN DEEP LEARNING
Chapter 22
β
GENERATIVE MODELS
Chapter 23
β
GRAPH NEURAL NETWORKS (GNNs)
Chapter 24
β
ADVANCED CNN
Chapter 25
β
ADVANCED NLP
Chapter 26
β
SELF-SUPERVISED LEARNING
Chapter 27
β
MODEL OPTIMIZATION & SCALING
Chapter 28
β
EXPLAINABLE AI (XAI)
Chapter 29
β
MULTIMODAL DEEP LEARNING
Chapter 30
β