Linear Algebra For Data Science & Machine Learning In Python

Learn Concepts of Linear Algebra and Implement using Python 3, Hands on Numpy, Pandas for Data Science & Linear Algebra

What you'll learn
Complete Understanding of Python from Scratch
NumPy Array, NumPy Operations
Pandasn and Numpy for Data Analysis
DataFrames, Pandas Series, Pandas Matrix
Learn Numpy and Pandas Library
Understand The Basics of Linear Algebra And Have A Solid Foundation In Linear Algebra
Understand how to use Python to do linear algebra operations
Understand Linear regression
Requirements
Basic High School Math
Description
In this course, We will explain the essentials of Linear Algebra and everything that you need to understand the basics of linear algebra as well as explain Python from Scratch. We will cover content such as:Python 3 Basics to Advanced LevelNumpy Library and Pandas LibraryMatrices and Linear System of EquationsLinear Regression with Python Numpy LibraryMatrix Operations using Python Numpy LibraryGaussian EliminationReduced Echelon Form and RREFMatrix AlgebraSpecial Matrices, Diagonal Matrices, and Inverse MatricesInverse Matrices and The Inverses of Transposed MatricesDeterminants and computing the Determinant Much more!By the end of this course, you should very comfortable with Python, Linear algebra, and be able to follow throw any Math which uses the Linear Algebra notation in Machine learning algorithms. You will also get answers to any questions that you might have for life. 

Overview

Section 1: Welcome to Course!

Lecture 1 Introduction

Section 2: Python Basics and Data Types

Lecture 2 Installation and Setup

Lecture 3 Basics

Lecture 4 Variables

Lecture 5 Data Types Introduction

Lecture 6 Numbers

Lecture 7 Strings Part 1

Lecture 8 Strings Part 2

Lecture 9 Strings Part 3

Lecture 10 Strings Part 4

Lecture 11 Lists

Lecture 12 Dictionaries

Lecture 13 Tuples

Lecture 14 Sets

Lecture 15 Booleans

Section 3: Statements, Functions and OOP in Python

Lecture 16 If, Elif and Else

Lecture 17 For loop

Lecture 18 While Loop

Lecture 19 Useful functions in Python

Lecture 20 Functions Part 1

Lecture 21 Functions Part 2

Lecture 22 Map, Filter and Lambda Expression

Lecture 23 Scope of Variables in Python

Lecture 24 Introduction of Object Oriented Programming

Lecture 25 Class and Attributes

Lecture 26 Methods

Lecture 27 Inheritance

Section 4: Data Analysis with NumPy and Pandas

Lecture 28 Introduction to NumPy

Lecture 29 NumPy Arrays

Lecture 30 NumPy Arrays : Indexing and Selection

Lecture 31 NumPy Operations

Lecture 32 Introduction of Pandas

Lecture 33 Pandas Series

Lecture 34 DataFrames Part 1

Lecture 35 DataFrames Part 2

Lecture 36 DataFrames Part 3

Lecture 37 Working with Missing Data

Lecture 38 Groupby Method

Lecture 39 Merging, Joining and Concatenating DataFrames

Lecture 40 Pandas Operations

Lecture 41 Reading and Writing Files

Section 5: Linear Algebra And Python

Lecture 42 Lecture 1 - Linear System of Equations

Lecture 43 Lecture 2 - Elimination Method

Lecture 44 Lecture 3 - Gaussian Elimination Part 1

Lecture 45 Lecture 4 - Gaussian Elimination Part 2

Lecture 46 Lecture 5 - Gaussian Elimination Part 3

Lecture 47 Lecture 6 - Applications of Gaussian Elimination

Lecture 48 Lecture 7 - Row Echelon Form

Lecture 49 Lecture 8 - Row Echelon Form 2

Lecture 50 Lecture 9 - Matrix Algebra 1

Lecture 51 Lecture 10 - Matrix Algebra 2

Lecture 52 Python 1 - Matrix Algebra in Numpy

Lecture 53 Lecture 11 - Special Matrices, Diagonal and Inverse Matrices

Lecture 54 Lecture 12 - Special Matrices, Diagonal and Inverse Matrices Part 2

Lecture 55 Lecture 13- Inverse Matrices Continued

Lecture 56 Lecture 14 - Inverses and Transpose

Lecture 57 Lecture 15 - Determinants

Lecture 58 Lecture 16 - Determinants 2

Lecture 59 Python 2 - Inverse, Determinant Calculat

Lecture 60 Lecture 17 - Computation of Determinants

Lecture 61 Lecture 18 - Linear Regression in Python

Computer Science Students Who Want To Learn More Linear Algebra,Students Who Want To Learn The Linear Algebra For Machine Learning and Deep Learning,Anyone Who Is Interested In Math And Wants To Study Linear Algebra,Data scientists who want to review their linear algebra,Anyone Who wants to learn Python for Data Science