AI Sciences

Introduction and Instructor

Hello World

Intro to data types

Numbers

Strings

Tuples

Lists

Dictionaries

Sets

Comparison operators

Logical oprator,user input, game

Decision Making (if,else,elif)

Decision making(nested if)

Better coding practice, completing the game

For loop

While loop

Simple functions

Boolian and value returning Function

Calculator project

Introduction to Machine Learning

Kids Vs Computer Learning

Dataset

Labels and Features

Outliars

Model and Training

Overfitting and Underfitting

Accuracy and Error

Formates of Data

Types of Learning

Modes of Learning

Clustering

Recap

Into and motivation

How Decision Trees and Random Forest Work

Pros and Cons of Random Forest

Introduction to the final Project

Using NumPy for Random Forest

Using Pandas for Random Forest (1)

Using Pandas for Random Forest (2)

Reading and Manipulating Dataset

Using Matplotlib for Data Visualization (1)

Using Matplotlib for Data Visualization (2)

Dealing with Missing Values

Outliers Removal

Categorical to Numeric Conversion

Quick Implementation of Random Forest Model

Feature Importance

Recursion

Structure

Importing Data, Helper Functions

Question and Partition

Impurity

Information Gain

Best Split

Leaf and Decision Node

How to Build Tree

Classify

Accuracy and Error

Concluding