Lecture starts from 36:20

At times I feel so lucky being born in this age of internet, Otherwise it was no way possible for me to learn from this legend of machine learning for free, looking at this career across academia and industry , he is a pioneer . It like learning integral calculus from Newton himself.

any non CS person watching this in 2024? I have a medical background and now trying to learn this shit. those who are trying too, all the best, cheers

is anyone who is starting this in june 2024??

I just love how humble and friendly this prof is. Big fan

I was having a hard week.. because I bought a course, and I was not able to understand things in deep. I came on u tube, and this came on my screen.... bro I felt like god just sent me something to make me happy. This is best thing happened. Thank you for the course.

I am thankful for Stanford and Dr. Andrew for making these lectures available on KZfaq. I am from a third world country where I cannot access such quality education. I am so grateful. God bless everyone

It’s a real honor to be able to listen to this lecture at home.

I just love how humble and friendly this prof is.

the way this man teaches is something which doesn't get you tired. you will watch him teach with a beaming smile on your face. thanks for this great class.

Thank you for uploading these videos even though it's 2023 today. U can always learn something from Andrew Ng, He's like Iron man's dad.

Thank you for making this world class education from a premium institute like Stanford available to us at free of cost, which otherwise was unthinkable for me to get. Really loved the way Professor Andrew Ng taught this lecture. Looking forward to learning so much from him. Thank you 🙏

We are truly grateful to Stanford University for providing these valuable lectures free of charge, which holds significant importance for those who may not have the means to access this level of education.❤❤

40:14 supervised learning 1:04:50 unsupervised learning 1:11:18 reinforcement learnin

I am grateful to Stanford University and wish these open courses to be up-to-date and continuous.

This is amazing. Machine Learning, AI and Data Science are the fulcrum on which our world turns and will continue to turn. Thank you Standford and Andrew Ng for this generosity of knowledge to our world.

Andrew Ng is a legend. I took his course on Coursera and I wish the course never ended. I have taking a lot of Machine learning courses but none of them compare to Andrew's. He made complex concepts look trivial and established a theoretical background ('Intuition' as he would say).

Congratulations for the great work you have done for the humanity

This lecture was amazing! Andrew Ng is such a great teacher and explains everything so clearly and intuitively. This video is the next best thing to being in the classroom with him! Thank you for sharing this valuable resource with us!

Thank you for explaining the concepts, purposes, and practical applications so clearly

05/07/2022 Lecture 1: well-posed learning problem is said to learn from experience E with respect to some task T and some performance measure P, if the performance on T, as measured by P, improves with experience E. See, not that complex!

AmaOng teaching ,just blessed to get such content for free.

Thank you for the course. It's very helpful for me ❤

This course is great for students who are learning Machine Learning or Deep Learning.

I am a 12th-grade student and really interested in machine learning. I did some basic math which is required in machine learning and am starting with this course today. I really liked the fact that the language which is used in this course is python. so excited to learn about this new branch. Will try my best to complete it. THANK YOU STANFORD FOR UPLOADING THESE LECTURES.

Just loved the introduction . May I ask if we you-tube watchers can also get the hold of notes which sir Andrew is talking about ? btw thank you making this course and video available to us !!

Huge respect and love to you sir🙏

every time I watch it I learn more

What amazing 75 minutes of my life!

oh my God, Stanford thank you so much..

This video on machine learning is an absolute gem! It beautifully captures the essence of this transformative field and showcases the incredible power and potential it holds. As someone fascinated by the intersection of data and technology, I found this video to be both informative and inspiring. The video did an excellent job of explaining the fundamental concepts of machine learning in a clear and concise manner. From supervised and unsupervised learning to neural networks and deep learning, it covered a wide range of topics, making it accessible to both beginners and those with some background in the field. The real-life examples and applications of machine learning were truly captivating. Seeing how it can be used to recognize patterns, make predictions, and provide valuable insights across various industries like healthcare, finance, and marketing was mind-blowing. It's amazing to witness how machine learning algorithms can analyze vast amounts of data and extract meaningful information to drive innovation and improve decision-making. The video also touched upon the ethical considerations surrounding machine learning, emphasizing the importance of responsible and unbiased use of these algorithms. It's crucial to be aware of the potential biases that can exist in data and to strive for fairness and transparency in the development and deployment of machine learning models. This reminder of the ethical dimensions added depth and thoughtfulness to the video's content. I truly appreciate the effort put into creating this video. The visuals, animations, and explanations were top-notch, making complex concepts easier to grasp. It's evident that the creator has a deep understanding of machine learning and a talent for effectively communicating it to a broader audience. Whether you're a beginner seeking an introduction to machine learning or someone looking to deepen their knowledge, this video is a must-watch. It not only provides a solid foundation but also instills a sense of awe and excitement for the possibilities that machine learning holds. Hats off to the creator for producing such an outstanding and educational piece of content!

Interesting and informative. Thank you Andrew.

This is an amazing opportunity for students like me . Long last stanford University

In today's time Andrew Ng is legend by his ML knowledge 🤓

thanks Andrew and Stanford this very interesting for me.

Wow, what a lecture!! How can I download these videos? Prof Andrew is phenomenal

I am going to record my self building a product hopefully a life changing project for everyone thanks for this course.

Thanks Stanford for this video

Excelente clase. Saludos desde Perú.

thank prof, it's clear explained

That's amazing. Done watching

5 topics of this class 1) Supervised Learning 2) Machine Learning Strategy 3) Deep Learning 4) Unsupervised Learning 5) Reinforcement Learning

Very nice lecture

Thanx for the lecture.

Very good lecture, I learned a lot, I hope I did watch this video way sooner. thank you

We Students don't have Teachers like this If we can have I'm sure We can make this world more and more and more Better.

I love Andrew Ng♡

Let's do this 💪

Thank you!

Notice that the voices of the audience are not distorted at all: Prof. Ng was giving these lectures to Darth Vader and a fellow group of storm troopers who recently developed an interest in machine learning.

lecture starts from 36:30

Thank you for this amazing course. It would be of great help if you can provide the problem statements as well. As in the links provided before requires making an account on Piazza so can you please provide them in some other format. Thank you

this is so cool, its like im in class.

It's very helpful for me ❤

Where can we find the homework and projects for CS 229 ?

I'd love to see the analytics for this video. The view count must've grown exponentially within the past 6months to 1 yr

Much better than my professor!

Great course

좋은 강의 감사합니다.

Easiest way of teaching ❤

When I searched for ML I got this and saw Abdre Ng, I just cliked it instantly. I just now him in face and I knew when I was a 12th grader in 2018 G.C that he is a pretty recognized neural network scientist.

00:06 CS229 Machine Learning provides the tools to become experts in machine learning 06:13 This class aims to make you an expert in machine learning 18:33 Form small groups for class projects and prioritize teamwork. 24:04 Communication with teaching staff and important logistical information 35:47 Machine learning tools can help remake the world and make it a better place. 41:50 Supervised learning involves learning a mapping from inputs to labels using different models. 54:29 Supervised learning using neural networks for self-driving cars. 1:00:34 Debugging the learning algorithm is crucial for building effective learning systems. 1:11:51 Reinforcement learning can be used to train robots and optimize their behavior.

Can someone kindly share the website on which i can get a copy of his book?thanks

Does any one figured if there are recorded session of TA discussions, going in details over the prerequisite concepts..

Are the recordings of the discussion sections available as well? I would like to review the prerequisites for this class!

Can anybody tell from where we can find note, they are not available on site which is given?

Well I couldn’t get the book he mentioned from the site, any help

Any way to get the problem sets? The links require log in credentials I guess linked to the course itself, and the first problem set seems to be missing at all..

Hi. First of all thank you Stanford for uploading these lectures on youtube. I am currently doing Professor Andrew's coursera ML specialisation. Shall I listen to these lectures after I completed that specialisation?

How can i get notes for these lectures?

The cs229 course website no longer have class notes and other resources, please update it asap. It will be very helpful.

Where are the discussion recordings?

As a beginner what do you need before start to watch this playlist ?? Is this lecture series cover all the basic concepts about ML??

Very nice learning.

10 mins could have been enough for that video. There is really nothing to miss here.

I love Stanford!

great ending statement about Newsom

are the discussion sessions on youtube?

Starting the course today After this lecture going to cover prerequisite so looking for friends reply

How can i get the book in 1:03:30. How know the URL of the website

Is it the full ml course ???

at what year is this course taught at Stanford?

I don't know if this video is being monitored but, is it possible to get the files for the handouts for the course?

Where can I get all the study materials of cs229 ?

Since he mentioned about the group project I naturally started think about who to work with on my group project but after he asked "How many of you this is your very first class at Stanford? raise your hand" I have realized I do not have any group project at Stanford. Wish I could be in there xd

Hey question, what math should I exactly understand as a background before I start learning this course?

1:05:01 unsupervised learning

Thank you for this great lecture. if there are any Stanford students pls help me to get the tutorials.

Amazing. Also, #UnintentionalASMR

where are the discussion sections recording?

The website name where we will find the book systematic engineering principle for machine learning by andrew ng is not clear can anyone share the site ?

Will he be using tensor flow in his course?

SMOOTH DELIVERY

guys ., is anyone know where to find the homework?

Where to find the homework content?

anyone know if there is recordings for the dicussion sessions that go over probability, statistics and such (being a while and do need some reminder) Thx

Is this really the whole machine learning course and I mean top to bottom? Free of cost?

was andrew ng's original ML playlist removed?? i cant find it anywhere

Lecture notes are not available to download. Can it be requested?

Nice