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.❤❤
I am thankful for Stanford and Dr. Andrew for making these lectures available on UA-cam. I am from a third world country where I cannot access such quality education. I am so grateful. God bless everyone
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.
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 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 thankful to Andrew Ng and Stanford University for providing such valuable ML lectures free of charge, which holds significant importance for those who are new in this domain as well as those who may not have the means to access this level of education.
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).
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'll never be able to afford a degree from Stanford but this way I can learn from the master himself. Thank you Stanford university and Professor Andrew for making this available.
No wonder Stanford produces scholars! I didnt even feel like skipping first 10 minutes because they were so motivational. Most profs in my country and my uni to be specific would talk bout timid things like focussing on getting a job. While Sir Andrew actually motivated about building startups, making innovative technology, revolutionizing sectors. When u have profs like this that truly understand you and motivate you, ofcourse you're gonna work harder to succeed
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.
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!
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!
you finished the entire playlist, also could you tell me how much does this course prepare you for getting job, like can you build ensemble models after this course?
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!
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.
earlier i thought of going with course posted on coursera but when i started this video randomly I was hooked to it. i am not preparing to learn anything before this but will note any thing that is told, pause and learn that and again come back to it kind of more active approach i am following here. may be this helps i have wasted a lot of time so that i will atleast get through it. wish me luck
Thank you for all these course making it available on youtube. Here in India Education is business and schools and colleges looting money from people under education. No quality education is provided in India that's the reason no new business or businessman, research centres and companies have been started in India. There's nothing Quality in India no Quality in any field absolutely zero.
I'm glad find this courses free, in my country it still less class to learn this thing. and I want to learn this subject to be my thesis topic, this will be the beginning of journey 😁
The differentiation of the what regression and classification are is audibly understandable. Learning machine learning to try to understand how the human brain works. Thank
Thank you for the exceptional Machine Learning course by Andrew Ng-it has been immensely valuable. Could you please consider adding a full Artificial Intelligence course? Such a resource would be greatly beneficial to many learners eager to explore AI further who donot have access to these courses
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 !!
As a complete beginner in machine learning, should I jump directly into these lectures, or are there other prerequisites besides statistics and calculus that I should consider?
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.
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
Hi there, thanks for your question! The prerequisites for this course include linear algebra, basic probability and statistics. You can view more about the course here: online.stanford.edu/courses/cs229-machine-learning You may also be interested in checking out the first problem set: cs229.stanford.edu/materials/ps0.pdf Hope this helps! :)
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..
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 ?
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
I like using Andrew Ng's Machine learning course at Stanford University. I have a Bachelor of Engineering, Computer Engineering from University of Michigan, usa. I also have a LLM Master of Laws from University of London & A PhD in Political Science from Tel Aviv, ISRAEL. I would to continue this Stanford Machine Learning course and complete the related Andrew Ng's Machine learning & Deep learning courses from Coursera. These courses are very good. Andrew Ng should write a Standard Textbook on AI, ML and DL based on his courses and knowledge to assist A student;Professor like Me.
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?
Hi there, thanks for your comment! After you feel confident about the foundational knowledge you've learned in the specialization, you will then likely get the most of out these graduate level course lectures. Happy learning!
Hi Robert thanks for your question! You can check out the course website here: cs229.stanford.edu/ and the recent syllabus with notes and slides: docs.google.com/spreadsheets/d/12ua10iRYLtxTWi05jBSAxEMM_104nTr8S4nC2cmN9BQ/edit?usp=sharing
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.❤❤
What wonderful feedback, thanks for your comment!
@@stanfordonline it will be wonderful to get the assignments of this course
@@tanushreebhattacharya7786 they have provided the problem sets on the link in the description
Piazza is nice. Thanks for the exposé.
What a wonderful feedback @@stanfordonline
I am thankful for Stanford and Dr. Andrew for making these lectures available on UA-cam. I am from a third world country where I cannot access such quality education. I am so grateful. God bless everyone
@@26d8 bro what are you talking about
where u from?
@@la_rayyy 🤨
Sameeee
I"m from a first world country (Canada) and I can't afford these lectures.
Lecture starts from 36:20
Thanks
hero
Thank god
many thanks
Thanks
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.
you are not alone ...
We shall dub him sir andrew
Lebnitz
It would be like Newton, if it was Yoshua Bengio or Yann LeCun or Geoffrey Hinton
Yeah.. we're so privileged to have these opportunities.
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.
It’s a real honor to be able to listen to this lecture at home.
Hey bro any previous knowledge is required for this course ?
@@ItihaasInsights1 no, he says he'll explain concepts along the way.
@@ItihaasInsights1 prerequisites 10:21
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 🙏
I just love how humble and friendly this prof is. Big fan
40:14 supervised learning
1:04:50 unsupervised learning
1:11:18 reinforcement learnin
This is better my than my own machine learning course
We are truly thankful to Andrew Ng and Stanford University for providing such valuable ML lectures free of charge, which holds significant importance for those who are new in this domain as well as those who may not have the means to access this level of education.
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).
Is it the same course on coursera ?
@@anand-arnaudpajaniradjane9722 not at all. This course is much more theoretical, the coursera one is focused on practice
@@JComprendsAuxMaths okay thanks a lot for your answer !
bro which should i complete first youtube or coursera
And how exactly did it help with your career? Were you able to apply this knowledge in any useful way?
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'll never be able to afford a degree from Stanford but this way I can learn from the master himself. Thank you Stanford university and Professor Andrew for making this available.
I am so grateful to be learning from a legend. Thanks to the legend himself and Stanford as well.
No wonder Stanford produces scholars! I didnt even feel like skipping first 10 minutes because they were so motivational. Most profs in my country and my uni to be specific would talk bout timid things like focussing on getting a job. While Sir Andrew actually motivated about building startups, making innovative technology, revolutionizing sectors. When u have profs like this that truly understand you and motivate you, ofcourse you're gonna work harder to succeed
Actually!😃
I am grateful to Stanford University and wish these open courses to be up-to-date and continuous.
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.
I have started this playlist from today, now I pray to God that I can finish the entire playlist till the last video.
Date: 22/9/2024
Which College? Dear😊
did you finish ?
how is the playlist and how is it going on your side
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.
❤thank uuuu
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!
hey I would like to know if this course is begginer friendly or not
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!
Yeah hes much better than the MIT guys.
What wonderful feedback, thanks for your comment!
you finished the entire playlist, also could you tell me how much does this course prepare you for getting job, like can you build ensemble models after this course?
hello bro,can you provide me a book which mentioned here .
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!
Huge THANKS to Stanford university and Dr Andrew Ng for giving us possiloty to liaten this classes
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.
Can we learn ML just having good command on python or do we need concept of data science too?
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
Memememe
cheers man best luck
me and it's so hard for me man!
How r u keeping up with it? I also have a non tech background
mememe!!! same
lecture starts from 36:30
Every lecture need this type of cmt tnx
Saved me minutes ❤
Thanks
earlier i thought of going with course posted on coursera but when i started this video randomly I was hooked to it. i am not preparing to learn anything before this but will note any thing that is told, pause and learn that and again come back to it kind of more active approach i am following here. may be this helps i have wasted a lot of time so that i will atleast get through it. wish me luck
This course is great for students who are learning Machine Learning or Deep Learning.
Thank you for all these course making it available on youtube. Here in India Education is business and schools and colleges looting money from people under education. No quality education is provided in India that's the reason no new business or businessman, research centres and companies have been started in India. There's nothing Quality in India no Quality in any field absolutely zero.
Let's not blame all, there are some teachers who I love to attend classes of
is anyone who is starting this in june 2024??
You're never wolk alone men it's never too late
Yeah just finished this now
✊
Here
Yes bro 😅
5 topics of this class
1) Supervised Learning
2) Machine Learning Strategy
3) Deep Learning
4) Unsupervised Learning
5) Reinforcement Learning
I'm glad find this courses free, in my country it still less class to learn this thing. and I want to learn this subject to be my thesis topic, this will be the beginning of journey 😁
The differentiation of the what regression and classification are is audibly understandable. Learning machine learning to try to understand how the human brain works. Thank
Fresh out of The Higher institution, Associate Degree in Mechanical Engineering Technology, want starting today.... hoping for the best.
Thank you so much Stanford!!!
What amazing 75 minutes of my life!
Lecture 1 completed!
Thank you for the exceptional Machine Learning course by Andrew Ng-it has been immensely valuable.
Could you please consider adding a full Artificial Intelligence course? Such a resource would be greatly beneficial to many learners eager to explore AI further who donot have access to these courses
hello ,can you provide me a book which mentioned here .
3:58 I work for a logistics company. Wasn't expecting him to mention it like that. It's definitely an industry that needs machine learning
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 !!
every time I watch it I learn more
This is an amazing opportunity for students like me . Long last stanford University
Thanks for our comment, glad to hear you're enjoying these lectures!
I am going to record my self building a product hopefully a life changing project for everyone thanks for this course.
4 years late but this is awesome to get on with 🔥
As a complete beginner in machine learning, should I jump directly into these lectures, or are there other prerequisites besides statistics and calculus that I should consider?
Anyone starting in june 2024,
Reply to my comment,
Lets do it together...👍
Wait what.... This is intro class at Stanford. Lord have mercy on my soul.
AmaOng teaching ,just blessed to get such content for free.
The legend himself
Thanks Stanford for this video
Easiest way of teaching ❤
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.
Starting in Sept 2024
Huge respect and love to you sir🙏
In today's time Andrew Ng is legend by his ML knowledge 🤓
Congratulations for the great work you have done for the humanity
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.
Where can we find the homework and projects for CS 229 ?
10:07 - prereqs
39:37 - Supervised learning (my bookmark)
Thank you for explaining the concepts, purposes, and practical applications so clearly
oh my God, Stanford thank you so much..
10 mins could have been enough for that video. There is really nothing to miss here.
thanks Andrew and Stanford this very interesting for me.
Let's do this 💪
Very good lecture, I learned a lot, I hope I did watch this video way sooner.
thank you
are you a beginner from 0? if no, can you recommend me a yt tutorial?
Thank you so much for this
thanks for providing this course .
Anyone from India 🇮🇳
Me bro 🇮🇳
Yes
❤
Wow, what a lecture!! How can I download these videos? Prof Andrew is phenomenal
Much better than my professor!
Interesting and informative. Thank you Andrew.
Thank you for the course. It's very helpful for me ❤
this is so cool, its like im in class.
As a beginner what do you need before start to watch this playlist ??
Is this lecture series cover all the basic concepts about ML??
I'd love to see the analytics for this video. The view count must've grown exponentially within the past 6months to 1 yr
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
Do we need data science concept to understand this course or we can understand having command on python?
where are you guts getting the resources for this course, I can't find the exercise and lectures in the above link.
Hey question, what math should I exactly understand as a background before I start learning this course?
Hi there, thanks for your question! The prerequisites for this course include linear algebra, basic probability and statistics. You can view more about the course here: online.stanford.edu/courses/cs229-machine-learning
You may also be interested in checking out the first problem set: cs229.stanford.edu/materials/ps0.pdf
Hope this helps! :)
@@stanfordonline Hi, are all the problem sets available for me? If so, were can I find them?
@@stanfordonlinelinear algebra, that is harder than calculus 2 isn’t it?
@@lenderzconstableYes but not by much
I love Andrew Ng♡
i am a beginner, should i learn from him , or should i go for some basics of ml first.
Hi there, you can learn the basics from Andrew in this 3 course specialization: www.coursera.org/specializations/machine-learning-introduction
Can anybody tell from where we can find note, they are not available on site which is given?
Can someone kindly share the website on which i can get a copy of his book?thanks
That's amazing. Done watching
Can someone tell if this entire course is theoretical or gives some practical knowledge too?
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 what's the prerequisites for this course? Like python, nupy, pytorch, calculus, statistics , probability etc... or all is taught in this course?
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 ?
I need a partner to coordinate with practice projects by following this course, will you?
Between all of this, the worse thing is Andrew Ng Course is no longer FREE?🙏
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
did you find it bro?
No I didn't :(@@Quester2023-xp7rb
Is there any group of written lectures where I can note these points ???
I like using Andrew Ng's Machine learning course at Stanford University. I have a Bachelor of Engineering, Computer Engineering from University of Michigan, usa. I also have a LLM Master of Laws from University of London & A PhD in Political Science from Tel Aviv, ISRAEL. I would to continue this Stanford Machine Learning course and complete the related Andrew Ng's Machine learning & Deep learning courses from Coursera. These courses are very good. Andrew Ng should write a Standard Textbook on AI, ML and DL based on his courses and knowledge to assist A student;Professor like Me.
Palestine*
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?
Hi there, thanks for your comment! After you feel confident about the foundational knowledge you've learned in the specialization, you will then likely get the most of out these graduate level course lectures. Happy learning!
Hi, Could you guide me where i can find that course exactly? Is that the beginner course?
till 34:00 for Stanford Student
From 34:00 for online student
I don't know if this video is being monitored but, is it possible to get the files for the handouts for the course?
Hi Robert thanks for your question! You can check out the course website here: cs229.stanford.edu/ and the recent syllabus with notes and slides: docs.google.com/spreadsheets/d/12ua10iRYLtxTWi05jBSAxEMM_104nTr8S4nC2cmN9BQ/edit?usp=sharing
The cs229 course website no longer have class notes and other resources, please update it asap. It will be very helpful.
It's Amazing.
Very nice learning.