AI Sciences

Introduction To Instructor

Introduction To Instructor

Introduction to Course

Focus of the Course

Focus of the Course

Packages to be Covered

Contents to be Covered

How to Speed up

Introduction to Feature in Data Science

Python is Important

Marking Facial Features

Feature Space

Features Dimensions

Features Dimensions- Lecture 8-Quiz

Features Dimensions-Lecture 8-Solution

Features Dimensions Activity

UCI ML Repository

Functions

Why Dimensionality Reduction

Activity-Dimensionality Reduction

Feature Dimensionality Reduction Methods

Feature Dimensionality Reduction Methods-Lecture 12- Quiz

Feature Dimensionality Reduction Methods-Lecture 12 -Solution

Why Feature Selection

Importance of Machine Learning

Feature Selection Methods

Filter Methods

Wrapper Methods

Embedded Methods

Search Strategy

Search Strategy

Forward Selection Search

Backward Elimination Search

Search Strategy Activity

Statistical Based Methods

Statistical Based Methods

Statistical Method-Low Variance

Statistical Method-T Score

Statistical Method-Chi-Square Score

Information Theoratic Methods

Similarity Based Methods Introduction

Similarity Based Methods Criteria

Activity- Feature Selection in Python

Python Implementation of Filter Method

Python Implementation of Wrapper Method

Python Implementation of Embedded Method

Python Implementation of Correlation Filter

Activity- Feature Selection

Introduction to Mathematical Foundation of Feature Selection

Intro to mathematical foundation

Closure Of A Set

Closure Of A Set-Lecture 27-Quiz

Closure Of A Set-Lecture 27-Solution

Linear Combinations

Linear Combinations- Lecture 28-Quiz

Linear Combinations-Lecture 28-Solution

Linear Independence

Vector Space

Basis and Dimensions

Coordinates vs Dimensions

SubSpace

SubSpace-Lecture 33-Quiz

SubSpace-Lecture 33-Solution

Orthonormal Basis

Orthonormal Basis-Lecture 34-Quiz

Orthonormal Basis-Lecture 34-Solution

Matrix Product

Matrix Product-Lecture 35-Quiz

Matrix Product-Lecture 35-Solution

Matrix Dimensions

Least Squares

Linalg Library

Rank

Eigen Space

Positive Semi Definite Matrix

Singular Value Decomposition SVD

Lagrange Multipliers

Vector Derivatives

Linear Algebra Module Python

Activity-Linear Algebra Module Python

Feature Extraction Introduction

PCA Introduction

PCA Criteria

PCA Properties

PCA Max Variance Formulation

PCA Derivation

PCA Implementation

PCA For Small Sample Size Problems(DualPCA)

PCA vs SVD

Kernel PCA

Kernel PCA vs ISOMAP

Kernel PCA vs The Rest

Encoder Decoder Networks For Dimensionality Reduction vs kernel PCA

Supervised PCA and Fishers Linear Discriminant Analysis

Supervised PCA and Fishers Linear Discriminant Analysis Activity

Dimensionality Reduction Pipelines Python Project

Encoder Decoder Networks For Dimensionality Reduction vs kernel PCA

Encoder Decoder Networks For Dimensionality Reduction vs kernel PCA

Supervised PCA and Fishers Linear Discriminant Analysis

Supervised PCA and Fishers Linear Discriminant Analysis

Kernel PCA vs The Rest

Kernel PCA vs The Rest

Dimensionality Reduction Pipelines Python Project

Dimensionality Reduction Pipelines Python Project

Categorical Features

Intro to Feature Engineering

Categorical Features Python

Categorical Features

Types of Encoding

Python implementation of Encoding

Where to use which Encoding

Intro to missing values

How to deal with missing values

Python implementation of Missing Values

Text Features

Image Features

Derived Features

Derived Features Histogram Of Gradients Local Binary Patterns

Feature Scaling

Activity-Feature Scaling