If there is anything I can be truly thankful for, it's education made available for free, especially from MIT.

*My takeaways:* 1. What is machine learning 8:13 2. How are things learned 9:55 3. Supervised learning and unsupervised learning 13:55 4. Clustering 15:01 5. Feature engineering 25:35 6. Minkowski metric: Manhattan distance and Euclidean distance 34:19 7. Classification example 43:42 - Confusion matrix and accuracy 46:50 - Other measurements: positive predictive value, sensitivity and specificity 49:25

I thank MIT for uploading such a valuable videos to the world.

This course is the BEST I’ve ever seen/heard explaining the concepts of Machine Learning/Deep Learning. Just simply awesome. MIT students are really lucky to have this professor. Makes me wish to be a college student again :-)

A very nice introduction. Thanks to Prof. Eric!

I can listen to this teacher 100 hours continuously. the way he spread words and his character.

Sir good evening , I am not related to this subject but your way of explaining subject matter is excellent .You are lecturer from top most institute in the world so I love to watch way of teaching process , methods and dealing with subject topics.your attitude and way of dealing contents is Very simple.Congratulations sir..

This is awesome! Thank you MIT.

I thank MIT, Prof Grimson, Prof Guttag, for the top quality, best and free lectures!

i think that eric is a tremendous teacher; really enjoy watching him explain stuff

Will definitely make a donation to MIT after I got my dream job.

Excellent, clear, granular fit as an intro. I hope to be able keep pace as a newbie. Many thanks.

A phenomenal professor who also makes learning fun. This is lecture number 11, which means that there are more lectures under this course, but I couldn't find the entire playlist on the channel.

I thank MIT for uploading such a valuable videos to the world. Will definitely make a donation to MIT after I got my dream job. I can listen to this teacher 100 hours continuously. the way he spread words and his character.

Excellent course and highly competent Professor! Thank you for sharing it online for free MIT, it really improved my fundamental understanding of machine learning.

This is so exceptional and simplified, am so grateful for this.

Brilliant teachers in MIT. I envy the students in this department.

Prof. Grimson is the best Professor ever.

Why I waisted my time on other video, when Prof. Eric is here.I am taking Andrew 's ML course and there I couldn't really understand overfitting and Prof. Eric very simply explains a hard idea with a nice example of Python and Cobra. Love U Prof. Eric :)

Brilliant. This is probably the best lecture on ML.

MIT classes, available for all, free for all, anywhere around the world. What a time to be alive.

God Bless MIT

blessed to have this free content. Thank you so much!

Gotta donate to MIT when I get a job really helpful video. Thanks!

Wonderful introduction to machine learning. Very accessible and inspiring. One slight correction. Frogs are ectotherms (cold-blooded)

The instructor is a gem of a person.

What an amazing video. So easy to understand. Thank you so much!

I don't always like his sense of humor but this is an excellent lecture by professor Eric Grimson

I'm glad I take such an insightful lecture. It was much easier to understand than the ones I've taken at my university. It covered the basic and fundamental concepts of machine learning in a way that beginners can grasp. Thank you for uploading.

When I was at university I learned to write Polymorphic code in C++. We then used Polymorphic code to write worms that would change the payload based on the system environment and vulnerabilities on that system. The actual application would change depending on the environment and the payload would be different for each environment. Given this definition, we was writing early ML programs back then.

Thank you, Professor Grimson. I appreciate the MIT OCW and I am doing a pseudo MIT challenge for myself.

What an amazing professor🙌

Now I feel confident, I can learn Machine Learning. Thank you Sir.

First read Bernard Lonergan's masterwork "Insight": 'Thoroughly understand what it is to understand, and not only will you understand the broad lines of all there is to be understood but also you will possess a fixed base, an invariant pattern, opening upon all further developments of understanding.'

Beautiful lecture. I was hooked the whole time.

Yes, This is what i was waiting for!

Thanks, SO happy to learn from MIT open courses

This is the best explanation I've ever seen about this topic

Excellent training, Thank you

absolutely astonishing lecture!

Always interesting, Great job! Thank you for sharing

Excellent professor! Thanks for sharing this video.

This is how you teach students! awesome explanations. without the explanation of the fundamental terminologies as he is doing here, machine learning becomes boring to learn

Excellent lecture

Sounds related to how we developed probability and statistics sums and formulas

Thanks Eric, you are greatly appreciated :)

Oh this handsome gentleman taught me Python, thank you MIT for such a great content!

Mit gerçekten affetmiyor abi muazzam bir anlatım

Good Sir, you know your stuff--well done! 👏

Good explanation . I really understand his explanation

A machine learning algorithm takes me to a machine learning course D:

This is GOD level content. Wow! I want to salute this man for explaining complex ideas in such simple terms. No wonder MIT grads learn so well :( I can only wish.

Thanks a lot, MIT ocw for providing these amazing courses for free!

Thank you very much for bringing us free online education, and special thanks to MIT, God Bless you

No wonder an MIT professor!! He lives up to his title. Good job!!

Siddharth Sankhe, Director, Consumer Insights, Nielsen talks about magnifying customer connections on Engati CX. He says that with the on going pandemic the economy has shrunk this is where CX comes into play and it will a very big and an important differentiator. ​@VSXY​

Professor Grimson is the best!

Thank You MIT

seven layers of protocol: application layer...etc,. stack, queue, linked list,...etc. top-down approach, bottom-up approach, dynamic programming,...etc. round robin search

Can't believe this is free. Awesome!!

Thanks MIT, THANKS ERIC!

That was really awesome.

One comment on a part of the lecture that sounded counterintuitive to me. In the football example (42:27) he was arguably working with four different types of football players, but professor Grimson was rejecting working with four clusters, being afraid of overfitting, in stead choosing three, while he was clearly aware of there being four different types of football players. I would have chosen four clusters to reflect the four different types of football players and start from there.

Awesome. Thank you, Sir.

GOD BLESS YOU SO MUCH.

amazing... thank you sir.

This is insightful, thanks for sharing 👍

Amazing class!

God bless mr. Grimson

Excellent Prof.

Nice voice and clear articulation

Excellent course, thank you.

Exceptional explanation!

Thanks sir becoz of u i got my point

Boy, tough crowd. Grimson is excellent.

Very well explained!

This was great thanks for sharing.

what a wonderful lecture

MIT thank You for sharing this for FREE! This is unbelievable that we live at the times when we can learn such things for free! Sad that most people are choosing tiktok instead of this knowledge

i find this lecture much much better ..(never mind the "than" part) :)

Thank you Prof. Jack Nicholson!

An update: this excellent course now available on EdX at www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-6 You can audit it free, or get it marked and get a diploma for something extremely low, USD$49 now, and likely to be under $149 if you're reading this in a couple of years. The EdX, Udemy, etc. effort is still pretty crude -- but it's a step up from just watching the videos. (The videos are available alongside, so it's sorta KZfaq Greek Amphitheatre Plus Plus, or MIT OCW struggles into the 1980's. Gettin' there...)

welcome back

awesome class

This guy was born to explain things

So far the best ML courses are this one (Eric's MIT), Andrew Ng's Stanford or coursera and Yaser Abu Mostafa of Caltech

Awesome

Great explanation

Kids should learn more about computers, how they work, history etc. adults as well can benefit by this.

That was an awesome lecture on Machine Learning. No wonder MIT tuition is so expensive ; )

Awesome!

I am very interested in machine learning but I feel like this course is above my scope of knowledge so far. Is there a course posted that would be a good introduction to the introduction to machine learning?

Thank you.

The way u teach is ❤❤

Really insightful

Awesome.

Thank you for the video ! Nicely explained !

Tough crowd. Great job, professor!

Thank you MIT

Thank you!