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Includes

05:39:16 Hours On demand videos

64 Lessons

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₹15000

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Description

What will i learn

Course content 05:39:16 Hours 64 lessons

Introduction

1 Lessons 00:06:09 Hours

Installation 00:06:09

Pandas

5 Lessons 00:57:42 Hours

Pandas Part1 00:09:29
Pandas Part2 00:11:05
Pandas Part3 00:14:44
Pandas Part4 00:11:34
Pandas Part 5 00:10:50

Numpy

3 Lessons 00:18:30 Hours

Numpy Introduction 00:04:39
Numpy Array 00:08:27
Numpy Array Index 00:05:24

Data Analysis

10 Lessons 01:05:01 Hours

Data Analysis Part 1: SuperMarket Sales Report 00:07:47
Data Analysis Part 2: SuperMarket Sales Report 00:04:40
Data Analysis Part 3: SuperMarket Sales Report 00:05:18
Data Analysis Part 4: SuperMarket Sales Report 00:05:35
Data Analysis Part 5: SuperMarket Sales Report 00:10:07
Data Analysis Part 6: SuperMarket Sales Report 00:06:35
Data Analysis Part 7: SuperMarket Sales Report 00:05:31
Data Analysis Part 8: SuperMarket Sales Report 00:05:31
Data Analysis Part 9: SuperMarket Sales Report 00:08:23
Data Analysis Part 10: SuperMarket Sales Report 00:05:34

Machine Learning

26 Lessons 02:19:47 Hours

Machine Learning Part 1 00:11:20
Machine Learning Part 2 00:09:35
Types of Data 00:06:05
Descriptive Data analysis 00:06:10
Measure of Center 00:08:24
Practice Question
Anaconda Setup 00:03:58
Seaborn Library 00:11:36
Seaborn Library Part2 00:09:22
ML Steps 00:06:19
Data Preprocessing 00:09:24
Univariate analysis and EDD 00:04:47
EDD in Python 00:03:36
Task
Outlier Treatment Part 1 00:06:12
Outlier Treatment 00:13:58
Outlier Treatment Part 2 00:08:11
Task
Missing Value Imputation Part 1 00:03:24
Missing Value Imputation Part 2 00:02:06
Task
Seasonality in Data 00:04:00
Variable Transformation 00:03:53
Task
Dummy Variable setting 00:07:27
Task

Classification Models

8 Lessons 00:14:14 Hours

Logistic Regression 00:00:00
Training a Simple Logistic Model in Python 00:00:00
Result of Logistic Regression 00:00:00
Task
Muliple Predictor 00:05:13
Task
Confusion Matrix 00:03:15
Confusion Matrix Part 2 00:05:46

Linear Discernment Analysis

3 Lessons 00:04:48 Hours

LDA 00:03:42
Linear Discernment Analysis Part2 00:01:06
Task

Test-Train Split

3 Lessons 00:11:43 Hours

Test-Train Split 00:06:15
Test-Train Split Part2 00:05:28
Task

K-Nearest Neighbors classifier

4 Lessons 00:12:10 Hours

KNN Part1 00:04:24
KNN Part2 00:05:36
Task
Summery 00:02:10

Project

1 Lessons 00:09:12 Hours

Bitcoin Prediction 00:09:12

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4 Courses

4393 Students

530 Reviews

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Linu Anna John

Mon, 20-Dec-2021

Python Professional