1.
Overview
Summary
2.
Table of Contents
Generative AI
3.
What is Generative AI?
4.
Machine Learning
4.1.
Deep Learning
4.2.
Neural Networks
4.2.1.
Neuron
4.2.2.
Perceptron
4.2.3.
Weights
4.2.4.
Features
4.2.5.
Bias
4.2.6.
Classification
4.2.7.
Regression
4.2.7.1.
Linear Regression
4.2.7.2.
Polynomial Regression
4.2.7.3.
Ridge Regression
4.2.7.4.
Lasso Regression
4.2.7.5.
Logistic Regression
4.2.8.
Multi-Layer Perceptron
4.2.9.
Generative Adversarial Networks
Models
5.
What is a Model?
5.1.
LLM
5.2.
Datasets
5.3.
VAE
5.4.
Training
5.5.
Inference
5.6.
Evaluation
5.7.
Decision Trees
5.8.
Support Vector Machines
RAG
6.
What is RAG?
7.
Embedders
Light
Rust
Coal
Navy
Ayu
Notes about AI/LLM/RAG
Introduction
Overview
Summary
Table of Contents
Generative AI
What is Generative AI?
Machine Learning
Deep Learning
Neural Networks
Neuron
Perceptron
Weights
Features
Bias
Classification
Regression
Linear Regression
Polynomial Regression
Ridge Regression
Lasso Regression
Logistic Regression
Multi-Layer Perceptron
Generative Adversarial Networks
Models
What is a Model?
LLM
Datasets
VAE
Training
Inference
Evaluation
Decision Trees
Support Vector Machines
RAG
What is RAG?
Embedders