Linear Programming For Data Science And Machine Learning

Learn linear programming by Sketching curves, Plotting Graphs and their application in data science and machine learning

What you'll learn
Coordinate system
Locations of points in coordinate system
Linear Inequalities
Practical examples of linear inequalities
Graphing of linear inequalities
Solution of linear inequalities
Properties of linear inequality
Linear programming
Objective functions
Optimal Solutions
Linear Programming theorem
Solution regions
Solution regions of constrains with respect to objective functions
Requirements
Basics of mathematics
Description
How to become a pro in Linear Programming?In this course, you will learn all about the mathematical optimization of linear programming. This course is very unique and has its own importance in its respective disciplines. Data science and machine learning study heavily rely on optimization. Optimization is the study of analysis and interpreting mathematical data under special rules and formulas. Thousands of students worldwide are searching this topic of Linear Programming but they can't find the complete courses in Linear Programming.The length of the course is more than 6 hours and there are a total of more than 4 sections in this course. The quality and quantity of the course are super and you will enjoy the course all the way during the course. The course is prepared according to the current needs of the students and I was much time asked to prepare this course and then finally I started working on it and now it is life. Many students around the globe are taking this type of course and there was nothing in the online learning platform including YouTube and I think it is good for Udemy that they have such types of courses.In the first section of the course, we have discussed the coordinate system to develop an understanding of the basics of linear programming. While in the second section you will master the basics and advance concepts of linear inequality and finally you will get jump into Linear Programming for Data Science and Business AnalysisThe question-answer section is available for the students where they can ask as many questions as they can ask and I will respond to each of your questions promptly. The more questions that you will ask the more are learning to master your concepts. It is found that the students who ask more questions are more likely to be favorite students in their learning perspectives.Linear optimization or linear programming is considered the mathematical study of data science and business analytics. Therefore the students which are good at mathematics can take this course in an efficient way. However, I have tried my best to complete each section in an easy way. The most important thing is when you are being asked for the questions as you can put as many you want then why not you should put? So just keep in touch with your instructor and don't feel shy or hesitant to talk with your instructor. Remember that I am teaching on Udemy for the past 3 years and have a total of 18 years of teaching experience. I am a master in applied mathematics and give solutions to the people where Math has its applications. I have changed the life of many students around the world from my experience and polishing my world which has math difficulty.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Coordinate System

Lecture 2 What is coordinate axis?

Lecture 3 Coordinate points of straight line

Lecture 4 Drawing a linear graph

Section 3: Linear Inequality

Lecture 5 What are Linear Inequalities

Lecture 6 Graphing Linear Inequalities

Lecture 7 Examples

Lecture 8 Example 2

Lecture 9 Solution and Graphing of Linear Inequalities

Lecture 10 Detailed Examples

Section 4: Linear Programming

Lecture 11 Linear Programming

Lecture 12 Optimal solution and objective function

Data science, machine learning, deep learning, artificial intelligence