Machine Learning Full Course | Learn Machine Learning | Machine Learning Tutorial | Simplilearn

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, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will help you learn different Machine Learning algorithms in Python. Linear Regression, Logistic Regression, K Means Clustering, Decision Tree, and Support Vector.

Below topics are explained in this Machine Learning course for beginners:
0:00 Table of contents
01:46 Basics of Machine Learning
09:18 Why Machine Learning
13:25 What is Machine Learning
18:32 Types of Machine Learning
18:44 Supervised Learning
21:06 Reinforcement Learning
22:26 Supervised VS Unsupervised
23:38 Linear Regression
25:08 Introduction to Machine Learning
26:40 Application of Linear Regression
27:19 Understanding Linear Regression
28:00 Regression Equation
35:57 Multiple Linear Regression
55:45 Logistic Regression
56:04 What is Logistic Regression
59:35 What is Linear Regression
01:05:28 Comparing Linear & Logistic Regression
01:26:20 What is K-Means Clustering
01:38:00 How does K-Means Clustering work
02:15:15 What is Decision Tree
02:25:15 How does Decision Tree work
02:39:56 Random Forest Tutorial
02:41:52 Why Random Forest
02:43:21 What is Random Forest
02:52:02 How does Decision Tree work-
03:22:02 K-Nearest Neighbors Algorithm Tutorial
03:24:11 Why KNN
03:24:24 What is KNN
03:25:38 How do we choose 'K'
03:27:37 When do we use KNN
03:48:31 Applications of Support Vector Machine
03:48:55 Why Support Vector Machine
03:50:34 What Support Vector Machine
03:54:54 Advantages of Support Vector Machine
04:13:06 What is Naive Bayes
04:17:45 Where is Naive Bayes used
04:54:48 Top 10 Application of Machine Learning

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➡️ About Post Graduate Program In AI And Machine Learning
This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features
- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered
- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

[shreyaskulkarni]

Dene waala jab bhi deta deta chhapar phad ke thankyou for such amazing course huge respect ✊🙏🏻🙏🏻🙏🏻

[imranshaikh]

It's a very great tutorial ever found on youtube, Thanks a lot for sharing your valuable time and knowledge. It would be great if would have put all the practice datasets in the description.

[robindong]

Simplilearn always provided us the best tutorials, great job, really love it.

[ganapathibalasubrahmanyam]

Refer Naive Bayes Method. Time Stamp 4:22:24: The probability of a Purchase on a weekday P(B) = P(Weekday) has been given as 11/30. Weekday stats show: Probability of Buy as 9/24. Please explain how to arrive at 11/30 for probability of buy.

[girishthendi]

I m 31 now, I m a complete fresher in machine learning and in python, I was working as a supermarket billing guy for the past 8 years. Can I have a future in big companies if I study this??

[kurtcobainfr]

This is a great tutorial! Very easy to follow for beginners. Thank you for this!
Could you please tell me how I can find the coefficient for the variable “State” in total? As now the variable has split into two and each of those has a separate coefficient.

[SandeepRana-xnmk]

Hi Sir,
In Linear Regression at 54:00, we have 4 input label column but we are getting (large no. of regression coefficients) that is slope values. Why ? We should get only 4 slope coefficient value.

[Siddharth-uozw]

#Scenario 1 answer supervised learning, Scenario 2 unsupervised, Scenario 3 supervised learning questions at 7:00

[warriorv]

I'm watching machine learning course on youtube is always recommend on my home

[devarpitasinha]

Is it possible to get the dataset? I want to implement the codes by myself. Thank you in advance.

[ajiththalachil]

This was very helpful. Well explained in detail and thanks for sharing the timelines as well. COuld you please provide me with the data set used in the tutorial.

[AbhishekMishra-nxro]

I love this channel than edureka because of animated explaination
Hats off to your working
❤️❤️

[brindhasenthilkumar]

Facebook - Supervised Learning
Netflix - Unsupervised Learning
Fraud detection - Supervised Learning

[fazalurrahman]

TYSM for uploading this, Efforts appreciated, it was great learning the whole course :) .
Can you guys please send me .csv file of data sets ?

[makindefunmilayo]

Hi, thanks for the tutorial, It is really helpful. Please could you send me the datasets used in this course. Thank you.

[syedrizwanali]

7:18 Scenario 1 & 2: unsupervise, Scenario 3: supervised

[ddoe]

Will watch this soon.
Very grateful to Simplilearn. Thank you so much for sharing your knowledge with us.🙏

[duhithashety]

Ppt was easy and impressive, and the course contents started from scratch and explained with sufficient examples thank you simplilearn

[sadrulalom]

It's really a great.. I can't believe how to make the learning simple... Thank you.. expected more videos

[SoftwareEngineering]

Make for us a video on how to make an API or an application using python and Sckit Learn library,

Because we will not just be doing it in Jupiter notebook,

Kindly make that video I will really appreciate