AI Study

Step 1 : Introduction & Linear Regression

Introduction to AI/ML/DL

Linear Regression with One Variable

Linear Regression with Multiple Variables

Step 2 : Logistic (Regression) Classification & Softmax Regression

Logistic (Regression) Regression

Softmax

Multinomial Logistic Regression

Step 3 : Practical Issues in ML/DL

Practical Issues in Machine Learning: Learning Rate, Pre-processing, Overfitting

Basic concepts of DL

Step 4 : Neural Networks

XOR problem and solution

Backpropagation

ReLU

Weight initialization

Dropout and Ensemble

Step 5 : CNN (Convolutional Neural Networks)

Concept of CNN

Stride and Zero-padding

Pooling

CIFAR10 classification