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