11. Introduction to Machine Learning

[@jmrbug9623]

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

[@hanumareddy5431]

LJ

[@yt-sh]

true that

[@vikatsybko4484]

Just remember, it is not free for them, someone pays for it to be available for us. So the best gratitude is a donation :)

[@alekseibuinyi]

@@vikatsybko4484 haha, nice joke)

[@leixun]

*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

[@maybe9357]

Thank you

[@leixun]

Kartik Verma you’re welcome

[@madylal]

Very helpful

[@leixun]

@@madylal Welcome to check out my research on my channel.

[@madylal]

@@leixun link please?

[@0xLych]

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

[@nicolareiman9687]

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

[@sreedharks]

me too Nicola

[@satyapriyapanda8765]

Very lucid, amazing way of expression and course content is very practical.

[@wiktormichalec5639]

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.

[@sololife9403]

could you explain more about :' the way he spread words and his character.' I like the way of him: calm, clear

[@paulushimawan5196]

Prof. Eric Grimson is one of the world's best lecturer.

[@leodexter191]

Is it 100% beginner friendly ?

[@jameswharton5259]

I wanted to express my gratitude for the detailed and engaging content. Thank you for breaking down complex concepts into digestible parts and providing clear examples. This lecture has significantly deepened my understanding of machine learning principles and practices.

[@ppvshenoy]

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 :-)

[@karthin8017]

If I had been taught by professors such as this, I wouldn't have dropped out of college

[@amine5169]

@Raymond Reddington Facts

[@Asdfgadv33423]

@@karthin8017 It's your fault, not the professors. Go back to University and finish it

[@aliceinwonderchen2423]

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

[@ConsciousnessExplored]

Me and you both brother

[@更雨晴]

​@@ConsciousnessExplored Me too

[@semtex6412]

how far along are you now?

[@memecombine]

@@semtex6412 he works at pied piper now

[@semtex6412]

@@memecombine 😂😂

[@kamalkumarmukiri4267]

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

[@leonzheng574]

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

[@ryandsouza9042]

God Bless MIT

[@fariss9743]

God Bless KZbin!! :)

[@Nizchul]

God Bless Internet! :D

[@VivekSolankiAqua]

God Bless "Electricity/Battery" :-P

[@robroux6074]

you mean the Institute.

[@ManojKumar-mf6mu]

god bless big bang

[@alienkishorekumar]

Prof. Grimson is the best Professor ever.

[@matiasrisso5917]

I completely agree. I've done his Intro to Computational Thinking course and it's been amazing, so clear and practical.

[@zAbdullahKhan]

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.

[@mitocw]

kzbin.info/aero/PLUl4u3cNGP619EG1wp0kT-7rDE_Az5TNd

[@kwubegharitony2044]

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

[@AlexAcostaB]

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

[@prashantsingh1096]

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 :)

[@Spectacurl]

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

[@saifnoorprottoy]

Diego Solis 😂😂

[@ShinjiCarlos]

Oh! Gosh!!! D: That is the proof of a conspiracy! Get those machines arrested! hahahahaha

[@280alex]

It wants to learn MOREEE

[@complex5372]

The machine is trying to reproduce!

[@rkalla]

LET IT LOVE YOU!

[@TimmmTim]

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

[@ariansergi7929]

hey would you please send a link where you learned python from him. :)

[@svktejasvi]

@@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!

[@anycatdessai]

Me too. On the Edx course.

[@winsmen009]

Me too! Loved his delivery of the course. Great professor! :)

[@Speed001]

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

[@blogushkumar3982]

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.

[@kosterix123]

I'm not that impressed. It does say what teaching quality you experienced btw. USA?

[@OEFarredondo]

Kosteri x we lead the world in cheeseburgers.

[@ramakanthrama8578]

@@kosterix123 No, India. Hope you understand why now.

[@krishivagarwal5189]

@@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.

[@flochforster22]

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

[@maxajames]

The instructor is a gem of a person.

[@aidanjohnwalsh2129]

The only reason I'm interested in machine learning is Astrology: a subject that doesn't require anyone's "beliefs" based on severely lacking information and awareness. At least computers are open to learning new things.

[@HjalmarGuitarMaster]

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

[@carsongutierrez7072]

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

[@naipahalcareerinstitute9100]

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..

[@ashamilan1661]

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

[@ShakespeareCafe]

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.'

[@Dibbbbaaaaa]

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​

[@austinjohn8713]

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

[@hedgeh0g7]

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

[@remotesuumo6673]

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.

[@retrofutur1st]

Professor Grimson is the best!

[@ryanchiang9587]

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

[@安保亮-l9h]

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.

[@cmc634]

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

[@jrdetka]

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

[@roodborstkalf9664]

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

[@mindblowingfactscompilatio6903]

I learned so much from watching this video.

[@Sasha-cg9cz]

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

[@ahmadalayan6866]

A very nice introduction. Thanks to Prof. Eric!

[@VictorAntonioLive]

Exceptional explanation!

[@suryateja_1902]

True that..!

[@johnthebeloved6598]

Second that!

[@mohamedfouzibenreguia8343]

Third that!!

[@rashi3502]

Four that

[@osamanadeem671]

fifth that

[@LD-zd5fr]

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

[@niceday2015]

Thanks, SO happy to learn from MIT open courses

[@JamesSusanka]

This is awesome! Thank you MIT.

[@fartzy]

This guy was born to explain things

[@pilipinay594]

Excellent professor! Thanks for sharing this video.

[@jasonh8212]

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

[@mdaustany]

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

[@MrArmas555]

Thank you Prof. Jack Nicholson!

[@vaiibhavkmr]

Thanks MIT, THANKS ERIC!

[@itsmylife8639]

Brilliant. This is probably the best lecture on ML.

[@qazaqtatar]

Nice voice and clear articulation

[@noshinarthi4716]

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

[@exitparadise2244]

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..

[@olutobajoel125]

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

[@mohammadfaruque4034]

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

[@roodborstkalf9664]

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.

[@computersciencestuff3405]

Beautiful lecture. I was hooked the whole time.

[@haleloi3018]

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

[@sifiso5055]

What an amazing professor🙌

[@ucheogbede]

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!

[@thezoneseeker9220]

ML seemed to based on a abundant resouses which in this case the data and cloud storage. It was more expensive in the past. Now technologies are advanced that the cost was reduced to be reached by anyone. I believe next step is to customs design preferable AI to self pleasurize.

[@anikgupta3929]

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

[@HackionSTx]

29:45 For those curious out there, a chicken is indeed a reptile. In fact, they're a dinosaur. Even better, all birds are dinosaurs and reptiles.

[@adamlee9347]

Can't believe this is free. Awesome!!

[@borgusmaximus]

Boy, tough crowd. Grimson is excellent.

[@abusaeed2051]

The way u teach is ❤❤

[@MoeSkirllz]

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

[@grenbell9329]

Mit gerçekten affetmiyor abi muazzam bir anlatım

[@TheDavidlloydjones]

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 KZbin Greek Amphitheatre Plus Plus, or MIT OCW struggles into the 1980's. Gettin' there...)

[@mrncomputer]

what a wonderful lecture

[@001khokhar]

Excellent lecture

[@55maxtube]

Always interesting, Great job! Thank you for sharing

[@harwinderkarwal]

Excellent Prof.

[@timothybohm8914]

This is awesome! Thank you MIT. Will definitely make a donation to MIT after I got my dream job.

[@greendot9106]

For those that read this, hope you have a nice day!

[@dewdop]

This video pleases the algorithm.

[@FlipHackingRealEstate]

excellent explanation

[@user-qj4zr1pj9y]

Thanks Modi ji , it was a great lecture !

[@bremsberg]

God bless mr. Grimson

[@willft520]

Tough crowd. Great job, professor!

[@mossadismoslembtw1704]

Shaggy

[@dav0625]

Excellent course, thank you.

[@waynelast1685]

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" ?

[@xxm321]

absolutely astonishing lecture!

[@audienceslove5742]

Since 2016 long time no see! E learning, youtube learning googling learning my bookmarks my informations my ideas my approach my life hacks my diy my inspirational informations

[@UD-Blackknight]

Excellent training, Thank you

[@mohamedabdo-dl9dd]

thanks to MIT --- very interesting course

[@RoyalBengalCub]

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[@rawiaelrashidy2139]

Very useful lecture. I think the axis titles are not in the right order

[@meljuncortes4420]

Good explanation . I really understand his explanation

[@patrick-8068]

Learning father​ must live The​ Father

[@celineguler]

glad there is turkish subtitles.

[@maoyanggavin5099]

welcome back

[@rahilarshad2456]

Humor should be a must in any scary ML lecture

[@dhruvbhoi803]

Amazingggggg MIT

[@kingsleyokoli1]

Really insightful

[@madandumrerijal1783]

awesome class

[@SethuIyer95]

Yes, This is what i was waiting for!

[@salsalsal999]

MIT is the best

[@syedsaqlainahmad637]

last testing example confused me b/w FP and FN