# How To Get Started With Machine Learning? | Two Minute Papers #51 ## Метаданные - **Канал:** Two Minute Papers - **YouTube:** https://www.youtube.com/watch?v=4h0uC9FPVMQ - **Дата:** 02.03.2016 - **Длительность:** 3:46 - **Просмотры:** 151,756 ## Описание I get a lot of messages from you Fellow Scholars that you would like to get started in machine learning and are looking for materials. Below you find a ton of resources to get you started! __________________________ The AI Revolution: The Road to Superintelligence on Wait But Why: http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-2.html Superintelligence by Nick Bostrom: https://en.wikipedia.org/wiki/Superintelligence:_Paths,_Dangers,_Strategies Courses: Welch Labs - https://www.youtube.com/playlist?list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU Andrew Ng on Coursera - https://class.coursera.org/ml-005/lecture Andrew Ng (YouTube playlist) - https://www.youtube.com/playlist?list=PLA89DCFA6ADACE599 Nando de Freitas (UBC) - https://www.youtube.com/playlist?list=PLE6Wd9FR--Ecf_5nCbnSQMHqORpiChfJf Nando de Freitas (Oxford) - https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu Nando de Freitas (more) - https://www.youtube.com/playlist?list=PLE6Wd9FR--EdyJ5lbFl8UuGjecvVw66F6 https://www.youtube.com/watch?v=PlhFWT7vAEw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw One more at Caltech - https://work.caltech.edu/telecourse.html Andrej Karpathy - https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC UC Berkeley - https://www.youtube.com/channel/UCshmLD2MsyqAKBx8ctivb5Q/videos Geoffrey Hinton - https://www.coursera.org/course/neuralnets Machine Learning specialization at Coursera - https://www.coursera.org/specializations/machine-learning MIT - http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/ Mathematicalmonk's course: https://www.youtube.com/watch?v=yDLKJtOVx5c&list=PLD0F06AA0D2E8FFBA&index=0 "Pattern Recognition and Machine Learning" by Christoper Bishop: http://research.microsoft.com/en-us/um/people/cmbishop/prml/ "Algorithms for Reinforcement Learning" by Csaba Szepesvári: http://www.ualberta.ca/~szepesva/papers/RLAlgsInMDPs.pdf A great talk on deep learning libraries: https://www.youtube.com/watch?v=Vf_-OkqbwPo&feature=youtu.be Two great sources to check for new papers: http://gitxiv.com/top http://www.arxiv-sanity.com/top Recent machine learning papers on the arXiv: http://arxiv.org/list/stat.ML/recent The Machine Learning Reddit: http://www.reddit.com/r/MachineLearning/ One more great post on how to get started with machine learning: https://www.quora.com/How-do-I-get-started-in-machine-learning-both-theory-and-programming/answer/Sebastian-Raschka-1 A great blog post on how to get started with Keras: http://swanintelligence.com/first-steps-with-neural-nets-in-keras.html A website with lots of intuitive articles on deep learning: http://neuralnetworksanddeeplearning.com/ A free book on deep learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville: http://www.deeplearningbook.org/ WE'D LIKE TO THANK OUR GENEROUS SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Vinay S. Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz The thumbnail background image was created by C_osett - https://flic.kr/p/sDTYmm Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/ ## Содержание ### [0:00](https://www.youtube.com/watch?v=4h0uC9FPVMQ) dear fellow Scholars this is 2minute papers with Caro I get a lot of messages from you fellow Scholars that you would like to get started in machine learning and are looking for materials words fail to describe how great the feeling is that the series inspires many of you to start your career in research at this point we are not only explaining the work of research scientists but creating new research scientists machine learning is an amazing field of research that provides us with in credible tools that help us solve problems that were previously impossible to solve neural networks can paint in the style of famous artists or recognize images and are capable of so many other things that it simply blows my mind however bear in mind that machine learning is not an easy field this field fuses together the beauty rigor and preciseness of mathematics with the useful applications of engineering it is also a fast moving field on almost any given day 10 new scientific papers pop up in the repositories for everything that I mention in this video there is a link in the description box and more so make sure to dive in and check them out if you have other materials that helped you understand some of the more difficult Concepts please let me know in the comments section and I'll include them in the text below first some ### [1:19](https://www.youtube.com/watch?v=4h0uC9FPVMQ&t=79s) Non Scientific Texts non-scientific texts to get you in the ### [1:22](https://www.youtube.com/watch?v=4h0uC9FPVMQ&t=82s) The Road to Super Intelligence mood I recommend reading the road to Super Intelligence on a fantastic blog by the name wait but why this is a frighten inly long article for many but I guarantee that you won't be able to stop reading it beware Nick bast's super intelligence is also a fantastic read after which you'll probably be convinced that it doesn't make sense to work on anything else but machine learning there is a previous 2-minute papers episode on artificial super intelligence if you're looking for a teaser for this book now let's get a bit more technical with some of the better video series and courses out there Welch Labs is an amazing YouTube channel with a very intuitive introduction to the concept of neural networks Andrew Inc is a chief scientist at B research in deep learning his wonderful course is widely regarded as the Pinnacle of all machine learning courses and is therefore highly recommended Nando def fras is a professor at the University of Oxford and has also worked with Deep Mind his course that he held at the University of British Columbia covers many of the more advanced concepts in machine learning in regarding books I recommend reading my favorite holy toome of machine learning that goes by the name of pattern recognition and machine learning by Christopher Bishop a sample chapter is available from the book if you wish to take a look it has beautiful typ setting lots of intuition and Crystal Clear presentation definitely worth every penny of the price I'd like to note that I am not paid for any of the book endorsements in the series when I recommend the book I genuinely think that it provides great value to you fellow Scholars about software libraries ### [3:01](https://www.youtube.com/watch?v=4h0uC9FPVMQ&t=181s) Software Libraries usually in most Fields the main problem is that the implementation of many state-of-the-art techniques are severely lacking well luckily in the machine Learning Community we have them in abundance I've linked a great talk on what libraries are available and the strengths and weaknesses for each of them at this point you'll probably have an idea of which direction you're most excited about start searching for keywords make sure to read the living hell out of the machine learning Reddit to stay up to dat and the best part is Yet to Come starting to explore on your own thanks for watching and for your generous support and I'll see you next time --- *Источник: https://ekstraktznaniy.ru/video/14865*