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Advance Artificial Intelligence
Chapter 1: Fundamental Intelligence Module
Lesson 1.1: Artificial Intelligence Concept
Lesson 1.2: Machine Learning Fundamentals
Lesson 1.3: Perceptron
Lesson 1.4: Neural Networks
Lesson 1.5: Gradient Descent Training
Lesson 1.6: Regularization Techniques of Neural Network
Lesson 1.7: Metric for Neural Network
Lesson 1.8: Neural Network Advancement
Chapter 2: Visual Intelligence Module
Lesson 2.1: Convolution Neural Network
Lesson 2.2: Computer Vision Tasks
Lesson 2.3: Object Detection
Lesson 2.4: YOLO
Chapter 3: Language Intelligence Module
Lesson 3.1: Recurrent Neural Network (RNN)
Lesson 3.2: Attention Mechanism
Lesson 3.3: Transformer
Lesson 3.4: Pretrain Language Model - BERT
Chapter 4: Generative Intelligence Module
Chapter 5: Temporal Intelligence Module
Chapter 6: Large Model Intelligence
Lesson 6.1: Basics of Large Language Model
Lesson 6.2: Training LLM
Lesson 6.3: LLM Prompting
Lesson 6.5: Knowledge Distillation (KD)
Lesson 6.6: Retrieval-Augmented Generation (RAG)
Lesson 6.7: GraphRAG
Chapter 7: Multimodal Intelligence Module
Lesson 7.1: Fusion and Alignment
Lesson 7.2: Vision Transformers (ViTs)
Lesson 7.3: Contrastive Language–Image Pretraining (CLIP)
Chapter 9: Reinforcement Intelligence
Lesson 9.1: Markov Decision Process (MDP)
Coding Module
Installing PyTorch on macOS Using Virtual Environment (venv)
Perceptron model using PyTorch to learn the OR gate logic
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advance-artificial-intelligence
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Chapter-3
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lesson-3.1
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Lesson 3.1: Recurrent Neural Network (RNN)
[root@master ~]# echo $WIP_PAGE
...👾Wip...
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