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. 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