Machine Learning Course in Hindi



Following topics are covered in this video:

01:06 - Introduction to Python

06:20 - Installation of Python

07:07 - Python Variables

12:37 - Python Tokens

46:42 - Data Types in Python

01:06:00 - Hands-on: Data Types

01:09:35 - Hands-on: Comprehensions

01:14:13 - Conditional Statements

01:15:43 - Hands-on: Conditionals

01:22:58 - Looping Statements

01:24:36 - Hands-on: Loops

01:31:03 - Functions in Python

01:32:52 - Hands-on: Functions

01:39:40 - Classes and Object

01:41:13 - File Handling in Python

01:47:28 - Python Machine Learning Libraries

01:49:32 - Machine Learning Process

01:54:01 - What is NumPy?

01:57:50 - Why NumPy over Lists?

01:59:28 - What is a NumPy Array?

02:00:32 - Applications of NumPy

02:01:24 - Create a NumPy array

02:03:48 - Array Initialization

02:08:22 - Array Mathematics

02:12:00 - Indexing and Slicing in NumPy

02:14:25 - Array Manipulation

02:16:46 - Hands-on: NumPy

02:26:13 - Pandas

02:27:22 - Introduction to pandas

02:29:23 - features of Pandas

02:31:43 - Data Structures in Pandas

02:33:03 - Pandas Series Object and DataFrames

02:37:12 - Merge, Join and Concatenate using DataFrames

02:40:50 - Importing Datasets

02:42:30 - Analyzing Datasets

02:44:34 - Cleaning the Datasets

02:48:12 - Manipulating the Datasets

02:53:10 - Hands-on: Pandas

03:13:50 - Introduction to Matplotlib

03:15:04 - Matplotlib Concepts

03:18:13 - Bar Plot

03:21:52 - Scatter Plot

03:23:39 - Histogram

03:25:07 - Hands-on: Matplotlib

03:41:40 - Introduction to Seaborn

03:44:04 - Seaborn Functions

03:46:14 - Countplots

03:48:54 - Heatmaps

03:51:05 - Hands-on: Seaborn

03:59:27 - Linear Regression

04:15:20 - Hands-on: Linear Regression

04:35:10 - Decision Tree

04:44:11 - Hands-on: Decision Tree



This Machine Learning Tutorial will comprise of the following topics:

Introduction- 0:00

Installing Pandas- 01:36

Python Basics and Data Structures- 09:53

Libraries in Python- 01:58:13

NumPy- 1:59:42

Pandas- 02:28:15

Matplotlib- 02:59:11

ML basics- 3:34:04

Linear Regression- 03:43:04

Logistic Regression- 03:59:47

Decision Tree- 04:11:11
























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Post On 2021-04-22