11. Introduction to Machine Learning
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- Опубликовано: 18 май 2017
- MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: ocw.mit.edu/6-0002F16
Instructor: Eric Grimson
In this lecture, Prof. Grimson introduces machine learning and shows examples of supervised learning using feature vectors.
License: Creative Commons BY-NC-SA
More information at ocw.mit.edu/terms
More courses at ocw.mit.edu
If there is anything I can be truly thankful for, it's education made available for free, especially from MIT.
LJ
true that
Just remember, it is not free for them, someone pays for it to be available for us. So the best gratitude is a donation :)
@@vikatsybko4484 haha, nice joke)
*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
Thank you
Kartik Verma you’re welcome
Very helpful
@@madylal Welcome to check out my research on my channel.
@@leixun link please?
I can listen to this teacher 100 hours continuously. the way he spread words and his character.
me too Nicola
Very lucid, amazing way of expression and course content is very practical.
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.
Me and you both brother
@@artofexistance Me too
how far along are you now?
@@semtex6412 he works at pied piper now
@@memecombine 😂😂
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 :-)
If I had been taught by professors such as this, I wouldn't have dropped out of college
@Raymond Reddington Facts
@@karthin8017 It's your fault, not the professors. Go back to University and finish it
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.
could you explain more about :' the way he spread words and his character.' I like the way of him: calm, clear
Prof. Eric Grimson is one of the world's best lecturer.
Is it 100% beginner friendly ?
A machine learning algorithm takes me to a machine learning course D:
Diego Solis 😂😂
Oh! Gosh!!! D:
That is the proof of a conspiracy! Get those machines arrested! hahahahaha
It wants to learn MOREEE
The machine is trying to reproduce!
LET IT LOVE YOU!
Prof. Grimson is the best Professor ever.
I completely agree. I've done his Intro to Computational Thinking course and it's been amazing, so clear and practical.
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.
ruclips.net/p/PLUl4u3cNGP619EG1wp0kT-7rDE_Az5TNd
God Bless MIT
God Bless RUclips!! :)
God Bless Internet! :D
God Bless "Electricity/Battery" :-P
you mean the Institute.
god bless big bang
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
A very nice introduction. Thanks to Prof. Eric!
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.
Brilliant teachers in MIT. I envy the students in this department.
MIT classes, available for all, free for all, anywhere around the world. What a time to be alive.
This is so exceptional and simplified, am so grateful for this.
The instructor is a gem of a person.
Brilliant. This is probably the best lecture on ML.
This is the best explanation I've ever seen about this topic
Excellent, clear, granular fit as an intro. I hope to be able keep pace as a newbie. Many thanks.
Excellent course and highly competent Professor! Thank you for sharing it online for free MIT, it really improved my fundamental understanding of machine learning.
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.
Gotta donate to MIT when I get a job really helpful video. Thanks!
Now I feel confident, I can learn Machine Learning. Thank you Sir.
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 :)
blessed to have this free content. Thank you so much!
Oh this handsome gentleman taught me Python, thank you MIT for such a great content!
hey would you please send a link where you learned python from him. :)
@@ariansergi7929 I guess it should be: courses.edx.org/courses/course-v1:MITx+6.00.1x+2T2018/course/. I learnt from there too. Absolutely inspiring course!
Me too. On the Edx course.
Me too! Loved his delivery of the course. Great professor! :)
Sounds related to how we developed probability and statistics sums and formulas
Thanks, SO happy to learn from MIT open courses
Beautiful lecture. I was hooked the whole time.
What an amazing video. So easy to understand. Thank you so much!
Excellent training, Thank you
Yes, This is what i was waiting for!
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.
Excellent lecture
Wonderful introduction to machine learning. Very accessible and inspiring.
One slight correction. Frogs are ectotherms (cold-blooded)
What an amazing professor🙌
No wonder an MIT professor!! He lives up to his title. Good job!!
Thank you, Professor Grimson. I appreciate the MIT OCW and I am doing a pseudo MIT challenge for myself.
Excellent professor! Thanks for sharing this video.
Can't believe this is free. Awesome!!
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
absolutely astonishing lecture!
Always interesting, Great job! Thank you for sharing
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.
I'm not that impressed. It does say what teaching quality you experienced btw. USA?
Kosteri x we lead the world in cheeseburgers.
@@kosterix123 No, India. Hope you understand why now.
@@ramakanthrama8578 India has some of the best teachers in the world, sadly they can't teach everyone one. Most teach in expensive private schools now or somewhere like IIT which has incredibly benefits for professors and researchers.
Good explanation . I really understand his explanation
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.'
Thank you very much for bringing us free online education, and special thanks to MIT, God Bless you
Thanks a lot, MIT ocw for providing these amazing courses for free!
Thanks Eric, you are greatly appreciated :)
This guy was born to explain things
Professor Grimson is the best!
Nice voice and clear articulation
Mit gerçekten affetmiyor abi muazzam bir anlatım
Exceptional explanation!
True that..!
Second that!
Third that!!
Four that
fifth that
Thanks MIT, THANKS ERIC!
Excellent course, thank you.
Good Sir, you know your stuff--well done! 👏
what a wonderful lecture
That was really awesome.
Excellent Prof.
Thank you Prof. Jack Nicholson!
This is insightful, thanks for sharing 👍
Boy, tough crowd. Grimson is excellent.
I learned so much from watching this video.
Amazing class!
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?
Very well explained!
Awesome. Thank you, Sir.
Thanks sir becoz of u i got my point
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.
Thank You MIT
i find this lecture much much better ..(never mind the "than" part) :)
This was great thanks for sharing.
seven layers of protocol: application layer...etc,.
stack, queue, linked list,...etc.
top-down approach, bottom-up approach, dynamic programming,...etc.
round robin search
That was an awesome lecture on Machine Learning. No wonder MIT tuition is so expensive ; )
Great explanation
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
amazing... thank you sir.
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
Really insightful
awesome class
Tough crowd. Great job, professor!
Shaggy
Kids should learn more about computers, how they work, history etc. adults as well can benefit by this.
excellent explanation
Thank you.
Great presentation; but next time the camera operator needs to focus more on the slides rather than the presenter. This way we can visually relate to what the presenter is saying. Anyways thanks to the prof for the great presentation!
hii i am final year student for that i have make project using machine learning, so we try lot ,to think idea but we don't get an idea, so can you suggest any idea that we can implement ....
@ Nikhil : If you carefully listen to the lecture it shouldn't be too hard to come up with lots of ideas. You should also take into consideration that the most labor intensive part is getting interesting data. As a student being under time pressure I would start searching the internet looking for reliable and interesting datasets that you have some affinity with. So if you for instance like cricket start looking for a good cricket dataset.
The way u teach is ❤❤
Humor should be a must in any scary ML lecture
Thank you!
Would like just to add program as input to the figure on 8'30" and output model instead of program, because the very task of ML is to write such program actually and deliver a model, far before packing it into another program. Please correct if this is wrong... :)
Awesome
this is the chief Hopper!
God bless mr. Grimson
Awesome!