Top ten Online Courses For Machine Learning [2020]

Looking at all the improvement taking vicinity in machine learning technology, here presenting a listing of on-line guides on Machine Learning that I believe can be of incredible assist for the peo…

Looking at all the improvement taking vicinity in machine learning technology, here presenting a listing of on-line guides on Machine Learning that I believe can be of incredible assist for the people who are aspiring to study and master Machine Learning technology.

Machine Learning Full Course - Learn Machine Learning

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:

1. Basics of Machine Learning - 01:46

2. Why Machine Learning - 09:18

3. What is Machine Learning - 13:25

4. Types of Machine Learning - 18:32

5. Supervised Learning - 18:44

6. Reinforcement Learning - 21:06

7. Supervised VS Unsupervised - 22:26

8. Linear Regression - 23:38

9. Introduction to Machine Learning - 25:08

10. Application of Linear Regression - 26:40

11. Understanding Linear Regression - 27:19

12. Regression Equation - 28:00

13. Multiple Linear Regression - 35:57

14. Logistic Regression - 55:45

15. What is Logistic Regression - 56:04

16. What is Linear Regression - 59:35

17. Comparing Linear & Logistic Regression - 01:05:28

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

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

20. What is Decision Tree - 02:15:15

21. How does Decision Tree work - 02:25:15

22. Random Forest Tutorial - 02:39:56

23. Why Random Forest - 02:41:52

24. What is Random Forest - 02:43:21

25. How does Decision Tree work- 02:52:02

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

27. Why KNN - 03:24:11

28. What is KNN - 03:24:24

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

30. When do we use KNN - 03:27:37

31. Applications of Support Vector Machine - 03:48:31

32. Why Support Vector Machine - 03:48:55

33. What Support Vector Machine - 03:50:34

34. Advantages of Support Vector Machine - 03:54:54

35. What is Naive Bayes - 04:13:06

36. Where is Naive Bayes used - 04:17:45

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

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

39. Machine Learning Interview Questions - 05:09:03

Machine Learning Tutorial - Learn Machine Learning - Intellipaat

This Machine Learning tutorial for beginners will enable you to learn Machine Learning algorithms with python examples. Become a pro in Machine Learning.

Mastering the Machine Learning Course would easily develop one's career. This is the reason why studying Machine Learning Tutorial becomes so important in the career of a particular student.
Making a part of the machine learning course would enact and studying the Machine Learning Tutorial would make one carve out a new niche.

The Common myths about Machine Learning by Rebecca Harrison

Machine learning is changing the dimensions of business in many industries. A report projects that the value added by machine learning systems shall reach up to \$3.9 Trillion by 2022.Machine lear...

Machine learning is proving it's worth in many industries like manufacturing, financial services, healthcare, and retail, to name a few. We hope that we have dispelled some of the myths associated with Machine Learning. It wouldn't be MLan incorrect to say that we have both overestimated and underestimated the potential of Machine learning systems.