This complete Machine Learning full course video covers all the topics that you need to know to become a master in the field of Machine Learning.

**Machine Learning Full Course | Learn Machine Learning | Machine Learning Tutorial**

It covers all the basics of **Machine Learning** (01:46), the different types of Machine Learning (18:32), and the various applications of Machine Learning used in different industries (04:54:48).This video will help you learn different Machine Learning algorithms in Python. Linear Regression, Logistic Regression (23:38), K Means Clustering (01:26:20), Decision Tree (02:15:15), and Support Vector Machines (03:48:31) are some of the important algorithms you will understand with a hands-on demo. Finally, you will see the essential skills required to become a Machine Learning Engineer (04:59:46) and come across a few important Machine Learning interview questions (05:09:03). Now, let's get started with Machine Learning.

Below topics are explained in this Machine Learning course for beginners:

Basics of Machine Learning - 01:46

Why Machine Learning - 09:18

What is Machine Learning - 13:25

Types of Machine Learning - 18:32

Supervised Learning - 18:44

Reinforcement Learning - 21:06

Supervised VS Unsupervised - 22:26

Linear Regression - 23:38

Introduction to Machine Learning - 25:08

Application of Linear Regression - 26:40

Understanding Linear Regression - 27:19

Regression Equation - 28:00

Multiple Linear Regression - 35:57

Logistic Regression - 55:45

What is Logistic Regression - 56:04

What is Linear Regression - 59:35

Comparing Linear & Logistic Regression - 01:05:28

What is K-Means Clustering - 01:26:20

How does K-Means Clustering work - 01:38:00

What is Decision Tree - 02:15:15

How does Decision Tree work - 02:25:15

Random Forest Tutorial - 02:39:56

Why Random Forest - 02:41:52

What is Random Forest - 02:43:21

How does Decision Tree work- 02:52:02

K-Nearest Neighbors Algorithm Tutorial - 03:22:02

Why KNN - 03:24:11

What is KNN - 03:24:24

How do we choose 'K' - 03:25:38

When do we use KNN - 03:27:37

Applications of Support Vector Machine - 03:48:31

Why Support Vector Machine - 03:48:55

What Support Vector Machine - 03:50:34

Advantages of Support Vector Machine - 03:54:54

What is Naive Bayes - 04:13:06

Where is Naive Bayes used - 04:17:45

Top 10 Application of Machine Learning - 04:54:48

How to become a Machine Learning Engineer - 04:59:46

Machine Learning Interview Questions - 05:09:03

Complete hands-on Machine Learning tutorial with Data Science, Tensorflow, Artificial Intelligence, and Neural Networks. Introducing Tensorflow, Using Tensorflow, Introducing Keras, Using Keras, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Learning Deep Learning, Machine Learning with Neural Networks, Deep Learning Tutorial with Python

Python has been the go-to choice for Machine Learning, Data Science and Artificial Intelligence developers for a long time. Python libraries for modern machine learning models & projects: TensorFlow; Numpy; Scipy; Scikit-learn; Theano; Keras; PyTorch; Pandas; Matplotlib; ...

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