Mathematics for Data Science and Machine Learning using R
Created by Eduonix Learning Solutions, Last Updated 05-Oct-2019, Language:English
Mathematics for Data Science and Machine Learning using R
Learn the fundamental mathematics for Data Science, AI &ML using R
Created by Eduonix Learning Solutions, Last Updated 05-Oct-2019, Language:English
What Will I Get ?
- Master the fundamental mathematical concepts required for Datas Science and Machine Learning
- Learn to implement mathematical concepts using R
- Master Linear alzebra, Calculus and Vector calculus from ground up
- Master R programming langauge
Requirements
- Basic knowledge of Statistics and Mathematics is required to complete the course
Description
Without a doubt, data science has become one of the most important fields in the current world. From banking to healthcare to business, it is essential for everyone and that is the main reason behind the significant increase in the demand of data science expert throughout the world. Considering all these things, we have designed this online course which teaches you all mathematics of data science including R programming language. R programming language was created especially for data analysis, performing statistics and graphical representation in a better way.
What makes this online tutorial unique?
Though several tutorials on data science are already available, this online course is one of its kind guide having hand-picked topics revolving around data science. It includes some of the essential concepts of foundational mathematics for data science using R programming language. You will explore numerous sections with over 9 hours of video content lectured by one of the world’s veteran statistician and data scientists, Timothy Young. He explains all the concepts in the most simplest way possible for easy and effective learning of mathematics behind data science.
This course includes -
- Introduction- Data Science, Machine Learning & R Programming Language
- Linear Algebra- Scalars, Vectors & Metrices
- Section Calculus- Function & tangent Lines, Derivatives
- Vector Calculus -
- Orthogonal Vectors and Linear Independence
- Eigenvectors and Eigenvalues
- Vectors Gradient Descent, and so much more!
It is clear that data science is becoming important for both developers as well as industries causing a significant increase in the demand of the experts. Like several others, if you are the one who is facing difficulties with all the mathematical concepts for data science then this is the right time and this online tutorial is the right course designed for exclusively for you!
Course Content
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Introduction
1 Lectures 00:01:01-
Introduction
Preview00:01:01
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Overview of R
3 Lectures 00:36:27-
Overview of R Workspace & Basic Commands
Preview00:22:50 -
LAB 1 Introduction
Preview00:02:27 -
LAB 1 Solution
00:11:10
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Linear Algebra
24 Lectures 04:11:52-
Scalars Vectors and Matrices
00:12:15 -
Application Scalars Vectors and Matrices
00:18:41 -
LAB 1 Intro Scalars Vectors and Matrices
00:01:38 -
LAB 1 Solution Scalars Vectors and Matrices
00:12:15 -
Vector Operations
00:11:59 -
Application Vector Operations
00:22:10 -
LAB 2 Intro Vector Operations
00:01:54 -
LAB 2 Solution Vector Operations
00:11:55 -
Matrix Operations Addition Subtraction Multiplication
00:17:40 -
Application Matrix Operations Addition Subtraction Multiplication
00:11:08 -
LAB 3 Intro Matrix Operations Addition Subtraction Multiplication
00:01:12 -
LAB 3 Solution Matrix Operations Addition Subtraction Multiplication
00:04:07 -
Matrix Operations Transposes and Inverses
00:11:33 -
Application Matrix Operations Transposes and Inverses
00:12:54 -
LAB 4 Intro Matrix Operations Transposes and Inverses
00:01:00 -
LAB 4 Solution Matrix Operations Transposes and Inverses
00:03:19 -
What is Linear Regression
00:11:27 -
Application What is Linear Regression
00:28:05 -
LAB 5 Intro What is Linear Regression
00:02:17 -
Lab 5 Solution What is Linear Regression
00:12:12 -
Matrix Representation of Linear Regression
00:12:28 -
Application Matrix Representation of Linear Regression
00:13:37 -
Lab 6 Intro Matrix Representation of Linear Regression
00:03:21 -
Lab 6 Solution Matrix Representation of Linear Regression
00:12:45
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Section Calculus
20 Lectures 03:36:21-
Functions and Tangent Lines
00:15:31 -
Application Functions and Tangent Lines
00:18:31 -
Lab 1 Intro Functions and Tangent Lines
00:01:51 -
Lab 1 Solution Functions and Tangent Lines
00:13:12 -
Derivatives
00:09:50 -
Application Derivatives
00:18:35 -
Lab 2 Intro Derivatives
00:02:38 -
Lab 2 Solution Derivatives
00:14:58 -
Optimization Using Derivatives Single Variable Functions
00:11:58 -
Application Optimization Using Derivatives Single Variable
00:10:22 -
Intro Optimization Using Derivatives Single Variable Function
00:01:26 -
Lab 3 Solution Optimization Using Derivatives Single Variable Function
00:08:15 -
Optimization Using Derivatives Two Variable Functions
00:10:42 -
Application Optimization Using Derivatives Two Variable
00:17:03 -
Lab 4 Intro Optimization Using Derivatives Two Variable Functions
00:02:25 -
Lab 4 Solution Optimization Using Derivatives Two Variable Function
00:05:02 -
Linear Regression The Calculus Optimization Perspective
00:19:59 -
Application Linear Regression The Calculus Optimization Perspective
00:16:41 -
Lab 5 Intro Linear Regression The Calculus Optimization Perspective
00:02:56 -
Lab 5 Solution Linear Regression The Calculus Optimization Perspective
00:14:26
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Tying it All Together Vector Calculus
16 Lectures 02:12:40-
Orthogonal Vectors and Linear Independence
00:10:32 -
Application Orthogonal Vectors and Linear Independence
00:13:15 -
Lab 1 Intro Orthogonal Vectors and Linear Independence
00:02:47 -
Lab 1 Solution Orthogonal Vectors and Linear Independence
00:12:07 -
Eigenvectors and Eigenvalues
00:12:47 -
Application Eigenvectors and Eigenvalues
00:09:50 -
Lab 2 Intro Eigenvectors and Eigenvalues
00:00:49 -
Lab 2 Solution Eigenvectors and Eigenvalues
00:04:42 -
Vectors Gradient Descent
00:10:02 -
Application Vectors Gradient Descent
00:10:51 -
Lab 3 Intro Vectors Gradient Descent
00:01:21 -
Lab 3 Solution Vectors Gradient Descent
00:12:50 -
Linear Regression The Gradient Descent Perspective
00:04:17 -
Application Linear Regression The Gradient Descent Perspective
00:17:55 -
Lab 4 Intro Linear Regression The Gradient Descent Perspective
00:01:15 -
Lab 4 Solution Linear Regression The Gradient Descent Perspective
00:07:20
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Eduonix Learning Solutions
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