Course curriculum

  • 1

    Let's get started here..!

    • Student GuideBook

    • Know About Your Trainer

    • Schedule, Timeline & Curriculum

    • Jupyter NoteBook Installation Guide

    • MACHINE LEARNING THE BIG FUTURE: INTRODUCTION AND SCOPE
  • 2

    Zoom Live Session Link

    • 10 OCT_ML_Zoom Live Session Link
  • 3

    Module 1

    • Machine Learning Live Session 1- 04/08/2020
  • 4

    Module 2

    • Machine Learning Live Session 2- 06/08/2020
  • 5

    Module 3

    • Machine Learning Live Session 3- 07/08/2020
  • 6

    Module 4

    • Machine Learning Live Session 4- 08/08/2020
  • 7

    Module 5

    • Machine Learning Live Session 5- 11/08/2020
  • 8

    Module 6

    • Machine Learning Live Session 6- 13/08/2020
  • 9

    Important Material

    • Assignment 1: Python Basics

    • Data Structure in Python

    • Control Flow and Loops in Python

    • Assignment 2: Practice and FAQ's

    • Practice Statistics Question

    • Statistics
  • 10

    Module 7

    • Machine Learning Live Session 7- 14/08/2020
  • 11

    Module 8

    • Machine Learning Live Session 8- 18/08/2020
  • 12

    Module 9

    • Machine Learning Live Session 9- 20/08/2020
  • 13

    Module 10

    • Machine Learning Live Session 10- 21/08/2020
  • 14

    Module 11

    • Machine Learning Live Session 11- 22/08/2020
  • 15

    Module 12

    • Machine Learning Live Session 12- 25/08/2020
  • 16

    Module 13

    • Machine Learning Live Session 13- 27/08/2020
  • 17

    Module 14

    • Machine Learning Live Session 14- 28/08/2020
  • 18

    Module 15

    • Machine Learning Live Session 15- 29/08/2020
  • 19

    Module 16

    • Machine Learning Live Session 16- 03/09/2020
  • 20

    Module 17

    • Machine Learning Live Session 17- 07/09/2020
  • 21

    Module 18

    • Machine Learning Live Session 18- 09/09/2020
  • 22

    Important Reading Material

    • Statistics

    • NUMPY

    • PANDAS
  • 23

    Reference Material

    • EDA Dataset

    • DataPerts - MATPLOTLIB

    • DataPerts - SEABORN

    • DataPerts - EDA

    • Session 1 - Types of Data, Measures of Central & Dispersion_stats

    • Session 2 - Skewness, Kurtosis, Descriptive Stats
  • 24

    Minor & Major Project

    • Problem Statement

    • Titanic.csv

    • Project Submission Link
  • 25

    Reference Material

    • Fruits

    • SLR_AdSpendVsSales

    • Multiple LR_Advertising_2_CategoricalVariables

    • InMovidu+DataPerts - SLR - AdSpendVsSales

    • Multiple LR_Advertising_Categorical

    • Logistic Regression

    • Subscription

    • KNN Classification_1 - IRIS

    • KNN Classification - Fruits
  • 26

    Important Material

    • 01 - Decision Tree Basics.html

    • 03- Decision Tree - Diabetes (1).html

    • 01 - Random Forest - Introduction.html

    • 02 - Random Forest Classification - Social Network Ads.html

    • 01 - Clustering - Introduction.html

    • KMeans_Case Study1_CreditCard.html

    • KMeans_Case Study2_Seeds.html

    • Hierarchical_Case Study1_CreditCard.html

    • Hierarchical_Case Study2_seeds.html

    • Diabetes.csv

    • Social Network Ads

    • creditcard.csv

    • seeds.csv