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    Linear Algebra For Data Science & Machine Learning In Python

    Posted By: ELK1nG
    Linear Algebra For Data Science & Machine Learning In Python

    Linear Algebra For Data Science & Machine Learning In Python
    Last updated 11/2021
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 4.40 GB | Duration: 10h 33m

    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