Lecture 18 - Epilogue

Epilogue - The map of machine learning. Brief views of Bayesian learning and aggregation methods. Lecture 18 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - itunes.apple.com/us/course/ma... and on the course website - work.caltech.edu/telecourse.html
Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, creativecommons.org/licenses/b...
This lecture was recorded on May 31, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.

[@louislu6910]

It is such a wonderful course, that I have viewed again and again. Thank you Yaser for bringing us to the fantastic world of machine learning!

[@Jotto999]

I am flabbergasted that this is just sitting here on KZbin, freely available. So many high-level concepts pertaining to machine learning, waiting for anyone who is able and willing. This professor is astoundingly bright, industrially-relevant, and delightfully descriptive. I even like his accent. I will be periodically coming back to watch parts again, trying to soak it in.

[@dhfromkorra]

easily the most inspiring course I will feel perpetually grateful for.

[@ilearnthings123]

Thank you, Professor Abu-Mostafa! It was a pleasure!

[@os8891]

I just finished this course , and i can't stress enough how i'm grateful to you professor Yaser for this course .. it was an ART.. i enjoyed every minute of these whole lectures ..

[@daGregor79]

Fantastic course, inspirational lecturer. One can feel the spirit of teaching that Richard Feynmann was known for. Thank you professor Yaser, thank you Caltech. Great, great job.

[@gowrithampi9751]

Now I'm so sad that he lost his best friend. I'll think of you Faiza, though I have no clue who you are. Thank you Professor Abu-Mostafa and everyone else from Caltech.

[@desitravellers2023]

Thank you Yaser and all the great people who contributed to this. No amount of praise is enough to appreciate the teachings of this course. With the prominence of deep learning techniques, of late the field of ML is turning into alchemy. The general trend for people now a days is to jump to "HOW" rather than asking the "WHY" i.e to seek for results without delving into the factors that made the results possible in the first place. For someone with enough scientific acumen, who asks "why" of ML, I hope this course will serve as a guiding light.

[@chrisroberts4599]

Thank you Yaser, that was incredible. My perceptron says this this lecture series will end up being a turning point in history, within a certain margin of error.

[@GuitarViolinCovers]

Can't express enough gratitude to Prof Yasser and all those that made this course content possible and accessible to all of us. After feeling lost and discouraged with my ML journey one chapter into Elements of Statistical Learning, I am once again full of inspiration and confidence. What a course.

[@MohammedAli-ss8sj]

Professor Yasser, no words can express how much I am grateful for you.Thank you so much for this great course. You made machine learning so friendly theoretically and practically.

[@navarretejairo1]

Thank you Prof. Yaser. If in the past, there were had more initiatives like this, we would live in a better world right now. Amazing production.

[@user-fg1ix4pj6i]

Көп-көп рақмет, керемет курс! Sending big thanks from Kazakhstan!

[@marawanish]

What a wonderful instructor, thanks a million Dr Yasser, Egypt is proud of you.

[@JonMcGill]

As an alum and former E&AS student, I really loved this video series format because it allowed me to watch it at my own pace. I never took this particular class when I was an undergrad, and it's too bad because I could have applied this knowledge greatly during my career. I guess that makes my E(out) and E(in) to be almost equally as bad - from now onwards, I'll be more vector supported and regularized... Thanks for the excellent lecture - loved the format (please do more)! :)

[@baravi2005]

This is just a brilliant lecture series on ML. It gives a deeper and fundamental understanding of the subject that you don't get in other courses. Kudos to Prof. Yaser, his team and Caltech for sharing them!!!

[@carlosnavarro9588]

What a journey! I'm not sure whether I'll keep walking this path, but what I've learned you can not pay with money. As Aristotle said, all men by nature desire to know. It's been already five years since I finished college and this course brought me back to that good old days, where my main occupation was learning for the sake of learning. Professor Yaser is such an inspiring, intelligent, amusing and enjoyable lecturer. Thank you all! :)

[@AndyLee-xq8wq]

Fantastic! Thank you all for providing this!!

[@adelmomorrison3517]

The course complimented well with the idiosyncrasies of Professor Yaser's teaching. Excellent job.

[@ksawery6568]

Life changing course, thank you so much!

[@maximilianmunch768]

Thank you so much. This public course is an awesome project. Great job!

[@xuemingqiang]

the best online course i have taken

[@pt77780]

You teach so well that you can preach about Human Learning next time!

[@ramanshah7627]

My deepest thanks to Yaser and everyone else involved for putting together a spectacular learning experience.

[@andresguzman5665]

Amazing and inspirational course. The professor encourages not only understanding but also love and interest for the field. I think that this is the most motivational ML course. Thank you so much for sharing this wonderful course. Thank you for your generosity.

[@sudhakarmadakaful]

It still feels relevant in 2020. Thank you.

[@namanjaswani8925]

I am so grateful for joining this course on youtube and watch such great prof. teach for free.

[@jjepsuomi9]

Everybody responsible with making this course available for everyone: You are an example to rest of the world! Thank you! =)

[@GigaDavy91]

Thank you! This is one of the best courses that i've ever followed.

[@hhj989]

This guy deserves 10M dollars for this course

[@DrDesideri0]

Great Professor, great lecture. The acknowledgments are simply moving!

[@neslihanarayit2350]

Thank you.. just thank you. this was incredible course and i will view this so much time, i am sure about it. my fav lecturer so far

[@barth05]

This whole course is pure gold. Thank you.

[@yonghwankim5217]

Great course, the most fundamental in machine learning.

[@YechielLabunskiy]

Thank you so much for this incredible course! All the concepts have been presented in a most clear manner, and masterfully woven into a single cohesive whole.

[@tradingmogador9171]

Thanks you Prof.YASER, you give me a head start in machine learning.

[@urielroque9203]

After taking different courses on data analysis and machine learning, I dont doubt to affirm that this course is the best one I have ever taken on those topics. Thanks Prof. Abu-Mostafa and course team for making that possible.

[@ferdaoussomrani2430]

This unbelievably fantastic! Thank you so much for this lectures, your passion and you amazing pedagogical approach! I am very grateful to all the team!

[@imranhussain1x]

What a magnificent course. Sets the standard at so many levels. Bravo to the Prof, Caltech and their entire team.

[@murtazaraja7510]

The course was rigorous indeed. I am glad to have stumbled upon this in the initial journey of understanding Machine Learning. Thank you Sir, thank you very much.

[@wujacob4642]

Thanks a lot to professor Yaser and everyone else involved in making this excellent online course. I found this course when I looked for SVM introduction. I knew little about machine learning then and found the SVM session very helpful. I found the whole series even more helpful when I know more about machine learning. Yaser gave the course in a practitioner's point of view, which make it very valuable, while at the same time, elaborated the theory in a very easy-to-understand way. Thank you.

[@QingkaiKong]

This is the best ML lectures online, like the professor said, this lecture is the essential part of ML trimmed by the Occam's Razor, thanks for all the effort, now I really have a clear picture of ML! Also the book (learning from data) is a great accompany of this lecture!

[@amrahmed2009]

Thank you for truly amazing course on conceptual and theoretical machine learning i have ever seen

[@xinxiong7348]

best machine learning course explained inside out， many thanks to the prof

[@mradoku]

Excelent course and inspiring Professor !! Thank you !!!

[@taitchif]

The course was incredibly rich and a provided a great source of information on machine learning. This is a prove that knowledge could be acquired from everywhere in the world thanks to the initiative of the Professor and his team and the progress of technology.

[@2rz2000]

Great course! Great teacher! Please do this for more courses! You're an amazing teacher! Thank you!!!

[@skpsun]

How wonderful that I found and watched such a great lecture series. Thank you professor. Thank you Caltech.

[@SIVERITOO]

One of the best lectures I've ever had the privilege to study, I really apreciate it.

[@michaeleva]

This is the best course that I ever have. Wonderful ! Thank Caltech and Prof. Abu !!!

[@bstiehl]

Thanks to everyone involved in providing this fantastic course!

[@TheLeQuangVu]

Excellent teacher, excellent course. Thanks Prof. Yaser.

[@rajkumarsinghakonwar]

Thank you Sir. I have experienced a great learning journey from this course. Regards RSK

[@TopicsInControlSystems]

All done but the final next week ;) This is such a great course and I am so lucky to have taken it through edX with all the support from Professor Abu-Mostafa and his staff of TA's. I can't say enough how great this course is. The homework is designed to make you learn and understand the lectures. The TA assistance was invaluable. Prof Mostafa is a great lecturer and entertaining as well. I feel so lucky to have had the opportunity to learn from him.

[@ZombieLincoln666]

While I did it, I finished watching all the lectures. Fantastic! But they could use an update - maybe just an extra lecture summarizing all the recent deep learning progress, which took off right after these lectures were recorded in 2012 (When Hinton first used deep CNNs on ImageNet). Mainly, that ReLUs are now used instead of tanh or sigmoids for the activation function in neural networks, and the common optimization algorithms like Adam, and dropout being used for regularization

[@brainstormingsharing1309]

Absolutely well done and definitely keep it up!!! 👍👍👍👍👍

[@weiruikong5139]

Hats off. Thank you Prof Yaser and thank you Caltech.

[@ljwljw21]

Finally finished the course, totally worth it!

[@Bing.W]

Fantastic professor. The world becomes better with the course.

[@LesterIngber]

I very much appreciated this enjoyable and informative course. I also very much appreciate that this course is open to anyone anywhere.

[@huihuazhao]

thank you! It's a great course. I learned a lot from. Thank you every one for making this happen.

[@devendrabendkhale6902]

Great course . Very much helpful. Great Work

[@jandal487]

Many thanks Prof. Mostafa for such a wonderful course. Each and every video lecture is a gem :)

[@lucunji8972]

Thank you so much... Really a great help for ML study during the horrible COVID-19.

[@bharathtvadhoola715]

Thanks a ton professor, thoroughly enjoyed the course and learnt a lot along the way too! highly recommend the course to anyone who is interested in the subject!

[@user-eq5es3it4k]

Thank you for your selflessness! So helpful. 谢谢！

[@mishas1653]

Thank you a lot for these amazing lectures. I feel like I returned back to my university classes.

[@1Osama9]

Best course. Best Professor!

[@AlexEx70]

Best ML course I've taken! Thank you! Hope there will be more courses from you, professor!

[@Celzo]

Thank you! I have learned so much from this course.

[@barbiemadeinussr]

The course was awesome! Everything is explained in a very clear way! And in this Lecture we finally saw Carlos, who read questions from on-line audience! :)

[@Nestorghh]

It's been an excellent course. Thank you very much CALTECH and Professor Yaser. I give this course 10 out of 10 points. Your examples are very clear and helpful.

[@anryxas1]

Thank you, great lectures and I have learned a lot.

[@michaelfeldmann7019]

Thank you very much for this great course and its excellent didactics!

[@bobwang111]

Thank you so much for providing this course!

[@antoniovazquez4900]

Outstanding professor!!!

[@andysilv]

Thank you for the course! It was a pleasure to study.

[@movax20h]

Awesome lectures. They were very helpful.

[@mohammadwahba3077]

Professor Yaser is the honor of Egypt

[@Darshanhegde]

Thanks Prof. Yaser, it was an amazing course I have ever taken :)

[@manakshah1992]

Amazing Lecture Series! Well organized and perfect for graduate students. Thanks a lot :)

[@9739865097]

Excellent lecture... Thank you for everything

[@ai.simplified..]

Such a good contents are avaleable for free 🤗 Warm sound, new things in data science that havent mentioned in other

[@samiheisa6428]

awesome !!! Thank you.

[@donm7906]

Thank you very much for sharing the knowledge to everyone.

[@ChristianLawsonNYC]

Great Course! Thank you so much! I bought the book too!

[@PeterNakeba]

Thanks Professor, this is the most exciting online study on complex and hard course which you have simplified, i was wondering how to do oral exam before my Prof. Farid Melgani at University of Trento, this has added value to my learning and retention of the concepts

[@Cr4y7-AegisInquisitor]

man this was a great journey

[@alessio.c7538]

Thank you so much!!! 🙏

[@pengyuewang93]

Great lecture, Thank you!

[@evanbruce1130]

Very inspiring，Thank you

[@imrozkhan111]

Thank you!

[@yastradamus]

Yaser, thanks a lot!

[@naziha1908]

Great Course!

[@jmea1000]

Great curse. Thanks

[@fradamor]

Very good lecture... The book should cover all topics in the on line course. Thank you professor.

[@srinivaschilukuri829]

This is like The Bhagvad Gita for Machine Learning !!! Both have 18 chapters :)

[@haoy80]

THANK YOU

[@chocolateblancomio]

I will always love you

[@u3s1r4]

Legend!