11. Introduction to Machine Learning
Вставка
- Опубліковано 18 тра 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 thank MIT for uploading such a valuable videos to the world.
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.
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 ?
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..
A very nice introduction. Thanks to Prof. Eric!
I thank MIT, Prof Grimson, Prof Guttag, for the top quality, best and free lectures!
This is awesome! Thank you MIT.
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.
ua-cam.com/play/PLUl4u3cNGP619EG1wp0kT-7rDE_Az5TNd.html
i think that eric is a tremendous teacher; really enjoy watching him explain stuff
MIT classes, available for all, free for all, anywhere around the world. What a time to be alive.
Brilliant teachers in MIT. I envy the students in this department.
This is so exceptional and simplified, am so grateful for this.
God Bless MIT
God Bless UA-cam!! :)
God Bless Internet! :D
God Bless "Electricity/Battery" :-P
you mean the Institute.
god bless big bang
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 :)
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.
Brilliant. This is probably the best lecture on ML.
I don't always like his sense of humor but this is an excellent lecture by professor Eric Grimson
blessed to have this free content. Thank you so much!
Wonderful introduction to machine learning. Very accessible and inspiring.
One slight correction. Frogs are ectotherms (cold-blooded)
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.
The instructor is a gem of a person.
Yes, This is what i was waiting for!
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! :)
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.
Sounds related to how we developed probability and statistics sums and formulas
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.
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.
What an amazing video. So easy to understand. Thank you so much!
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.
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
Thanks, SO happy to learn from MIT open courses
Thank you, Professor Grimson. I appreciate the MIT OCW and I am doing a pseudo MIT challenge for myself.
What an amazing professor🙌
Thanks Eric, you are greatly appreciated :)
No wonder an MIT professor!! He lives up to his title. Good job!!
Thanks a lot, MIT ocw for providing these amazing courses for free!
absolutely astonishing lecture!
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.
Exceptional explanation!
True that..!
Second that!
Third that!!
Four that
fifth that
Good Sir, you know your stuff--well done! 👏
This is the best explanation I've ever seen about this topic
Can't believe this is free. Awesome!!
Always interesting, Great job! Thank you for sharing
Mit gerçekten affetmiyor abi muazzam bir anlatım
Thanks MIT, THANKS ERIC!
Excellent professor! Thanks for sharing this video.
Excellent training, Thank you
seven layers of protocol: application layer...etc,.
stack, queue, linked list,...etc.
top-down approach, bottom-up approach, dynamic programming,...etc.
round robin search
Thanks sir becoz of u i got my point
Thank you very much for bringing us free online education, and special thanks to MIT, God Bless you
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
Excellent lecture
Professor Grimson is the best!
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?
Good explanation . I really understand his explanation
Thank You MIT
Boy, tough crowd. Grimson is excellent.
GOD BLESS YOU SO MUCH.
That was an awesome lecture on Machine Learning. No wonder MIT tuition is so expensive ; )
Tough crowd. Great job, professor!
Shaggy
That was really awesome.
So far the best ML courses are this one (Eric's MIT), Andrew Ng's Stanford or coursera and Yaser Abu Mostafa of Caltech
This guy was born to explain things
This is insightful, thanks for sharing 👍
Awesome. Thank you, Sir.
i find this lecture much much better ..(never mind the "than" part) :)
amazing... thank you sir.
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... :)
Amazing class!
God bless mr. Grimson
Humor should be a must in any scary ML lecture
Thank you Prof. Jack Nicholson!
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
Nice voice and clear articulation
20:40 Isn't it a better idea to draw a linear line through the data, and the perpendicular to that line would be the "dividing line" ?
this is the chief Hopper!
Excellent course, thank you.
welcome back
Kids should learn more about computers, how they work, history etc. adults as well can benefit by this.
Excellent Prof.
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 UA-cam Greek Amphitheatre Plus Plus, or MIT OCW struggles into the 1980's. Gettin' there...)
Awesome
I am looking for the playlist for all the courses associated with Introduction to Computational Thinking and Data Science. Could anyone share a link? Thanks
The way u teach is ❤❤
As always, there is a reading assignment. Chapter 22 of the book gives you a good start on this. Can you someone please tell me which book he is referring to? Thank you
The textbook is Guttag, John. Introduction to Computation and Programming Using Python: With Application to Understanding Data. 2nd ed. MIT Press, 2016. ISBN: 9780262529624. Via MIT Press mitpress.mit.edu/9780262529624 or via Amazon www.amazon.com/exec/obidos/ASIN/0262529629/ref=as_at/mitopencourse-20 See the course syllabus for more information at ocw.mit.edu/6-0002F16.
You have it on the internet, FREE. Search John Guttag introduction to computer science pdf.
note on astrology: it still is a valid indicator IF a person lives most/all of their life in synchrony with the cycles of the sun and moon. Has to do with memory and when memories are made + the type of Light that those memories were made in..
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!
Very well explained!
what a wonderful lecture
Awesome!
This is such an awesome video! Btw I'm not a pats fan (go cowboys! lol) but I love how at one point prof points out Gronk and Bennett in his example. xD