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Ask HN: Best introductory video courses on ML and Deep Learning?

• mindcrime 9y ago
  http://www.fast.ai/ http://www.fast.ai/ https://www.udacity.com/course/intro-to-machine-learning--ud120 https://www.udacity.com/course/intro-to-machine-learning--ud... https://agi.mit.edu/ https://agi.mit.edu/ https://www.youtube.com/watch?v=eLbMPyrw4rw&list=PL6EE0CD02910E57B8 https://www.youtube.com/watch?v=eLbMPyrw4rw&list=PL6EE0CD029... https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r... https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rB...
  • igravious 9y ago
    fast.ai Making neural nets uncool again. fast.ai is dedicated to making the power of deep learning accessible to all.[0] Udacity. Intro to Machine Learning: Pattern Recognition for Fun and Profit[1] MIT 6.S099: Artificial General Intelligence[2] Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, Indian Institute of Technology, Kharagpur[3] DeepMind. Reinforcement Learning Course by David Silver[4] Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition.[5] [0] http://www.fast.ai/ http://www.fast.ai/ [1] https://eu.udacity.com/course/intro-to-machine-learning--ud120 https://eu.udacity.com/course/intro-to-machine-learning--ud1... [2] https://agi.mit.edu/ https://agi.mit.edu/ [3] https://www.youtube.com/watch?v=eLbMPyrw4rw&list=PL6EE0CD02910E57B8 https://www.youtube.com/watch?v=eLbMPyrw4rw&list=PL6EE0CD029... [4] https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r... [5] https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rB...
• trias 9y ago
  this talk really enlightened me: https://www.infoq.com/presentations/neural-networks-introduction https://www.infoq.com/presentations/neural-networks-introduc... it is not a full course, but more an introduction.
• oscgonfer 9y ago
  I took the coursera specialisation one week ago. It takes you from the very basics to some more complex modules like keras or tensorflow. If you are into it and have time, the whole 4 courses can be done in the free week: https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning
• FullMtlAlcoholc 9y ago
  https://cs231n.github.io/ https://cs231n.github.io/
• nl 9y ago
  Fast.ai
• jack_pp 9y ago
  I've learned a ton from https://www.kadenze.com/courses/creative-applications-of-deep-learning-with-tensorflow/info https://www.kadenze.com/courses/creative-applications-of-dee...
• TheAlchemist 9y ago
  If you speak french, I would recommend Hugo Larochelle channel: https://www.youtube.com/user/hugolarochelle https://www.youtube.com/user/hugolarochelle
• visarga 9y ago
  Have you tried Andrew Ng's course? And I don't mean the one from the start of Coursera, but the original Stanford ML Course he taught at the blackboard. This ML course has all the math done by hand instead of skipped over. https://www.youtube.com/view_play_list?p=A89DCFA6ADACE599 https://www.youtube.com/view_play_list?p=A89DCFA6ADACE599
  • WhitneyLand 9y ago
    bad link?
    • evex 9y ago
      https://www.youtube.com/playlist?list=A89DCFA6ADACE599 https://www.youtube.com/playlist?list=A89DCFA6ADACE599
• nshr 9y ago
  Fast.ai, you can checkout the forum here: http://forums.fast.ai/ http://forums.fast.ai/
• alexnewman 9y ago
  As much as I love Ng, I vastly prefer Hinton’s lectures. Something about that English accent.
• aficionado 9y ago
  Ideal to practice, learn, and teach machine learning: https://bigml.com/ml101 https://bigml.com/ml101 https://bigml.com/education/videos https://bigml.com/education/videos
• aaronsnoswell 9y ago
  If you're interested in learning Reinforcement Learning, then I can't recommend David Silver's lecture series highly enough. Youtube videos and slides are available for the entire thing. http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html
  • deepGem 9y ago
    I wouldn't really classify this as an introductory course. Some background in A* search, Markov processes etc is required. David has a fantastic narration style and this is one of those courses where I had to step out because I had other responsibilities and not because I got bored with the content.
• ivan_ah 9y ago
  I found the "Bay Area Deep Learning School" 2-day lecture series to be very good: https://www.youtube.com/watch?v=eyovmAtoUx0 https://www.youtube.com/watch?v=eyovmAtoUx0 https://www.youtube.com/watch?v=9dXiAecyJrY https://www.youtube.com/watch?v=9dXiAecyJrY
• joshuaeckroth 9y ago
  If you want to see projects coded in Python (random forests, word2vec, convolutional neural nets), I recently finished producing this set of videos: https://www.packtpub.com/big-data-and-business-intelligence/python-artificial-intelligence-projects-beginners-video https://www.packtpub.com/big-data-and-business-intelligence/...
• jacek 9y ago
  Not a video course, but an excellent book: "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Aurélien Géron. Provides a gentle and high quality introduction to Machine Learning with practice from the very beginning. I wish I had this book when I was starting. It explains everything from data engineering, through how algorithms work, to practical applications. Everything in Python 3, covering pandas, scikit-learn, tensorflow. It is absolutely wonderful! [1] http://shop.oreilly.com/product/0636920052289.do http://shop.oreilly.com/product/0636920052289.do
  • colmvp 9y ago
    As a person who did a lot of Deep Learning... learning in 2017, I think this was my favorite. Fast.ai was fine, but I felt like most of my learning for the things I cared about came from reading research papers, watching Karpathy's CS231n lectures, and blog posts that went into detail on particular concepts. But when at certain points I felt confused on certain concepts, Geron's book did a pretty good job explaining things slowly and in great detail, especially with respects to the code he wrote. It's still a book I'll pick up for 20-40 minutes every other day to help my mind recall about how something works. Funnily enough, I've spent the last few months reading Sutton/Barto's Intro to Reinforcement Learning (along with Silver's lectures on DeepMind's YouTube Channel) and only realized Geron touches upon RL a little bit in the latter part of the ML book.
• kmax12 9y ago
  One important skill you will need is feature engineering. Formal methods for it aren’t typically in ML ciriculums, but it’s worth understanding if you’re interested in applications if ML. Deep learning addresses it to some extent, but isn’t always the best choice if you don’t have image / text data (eg tabular datasets from databases, log files) or a lot of training examples. I’m the developer of a library called Featuretools (https://github.com/Featuretools/featuretools https://github.com/Featuretools/featuretools) which is a good tool to know for automated feature engineering. Our demos are also a useful resource to learn using some interesting datasets and problems: https://www.featuretools.com/demos https://www.featuretools.com/demos
  • cuchoi 9y ago
    I am playing with an encrypted dataset, so this comes very useful. Any tips on how to take advantage of it or about its strengths and weaknesses?
• daniyalnawaz 9y ago
  Andrew Ng's deeplearning.ai course is pretty accessible for beginners.
• FabHK 9y ago
  I liked Yaser Abu-Mostafa's Caltech ML course. A bit dated (2012), but solid introduction to the basics (such as VC dimensions). However, given your stated preferences, other recommendations (such as fast.ai) are probably better suited. https://work.caltech.edu/telecourse.html https://work.caltech.edu/telecourse.html
  • Eridrus 9y ago
    I found this course pretty interesting, since it gives some perspective on what sorts of guarantees people want that DL doesn't provide, but I wouldn't necessarily recommend starting with it unless you have a theory bent.
• DLTarasi 9y ago
  I'll give another recommendation for http://www.fast.ai/ http://www.fast.ai/ I went through the first phase of the course as an intro to AI/DL and thought it was really great from a high-level perspective. If you have a decent understanding of Python you'll have a working model running on AWS within the first few hours of the course which is very rewarding. It does a better job than I expected explaining the underlying intuition of the math, but doesn't dive deep into the actual formulas. There are obviously tradeoffs to this approach and if you want to continue in the field you'll need to do something to fill in this background, but as far getting your hands dirty and understanding the basics I really liked the fast.ai approach.
  • hackernewsacct 9y ago
    As a beginner I cannot recommend this class in its current form. The first lecture with its setup walk through is outdated and I have trouble understanding how to do a work around.
    • tinymollusk 9y ago
      Part 1v2 was just released, it uses pytorch. Check it out, I was in the fall fellowship and can heartily recommend it.
      • hackernewsacct 9y ago
        This is welcomed news, thank you for the update. Can you link to v2? On the site I just see part 1, v1 with the AWS set up. This is the beginner unfriendly/outdated one I am referring to, and I don't see the updated version you're referring to.
        • tinymollusk 9y ago
          I just checked the course forum, and Jeremy asked us not to share on high traffic sites until theyve finished the new website. I think it'll be out within a week or so, so check the fast.ai site for updates. Should be soon!
• max_ 9y ago
  MIT 6.034 Artificial Intelligence, Fall 2010 https://www.youtube.com/watch?v=TjZBTDzGeGg&list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi https://www.youtube.com/watch?v=TjZBTDzGeGg&list=PLUl4u3cNGP...
• shrumm 9y ago
  tried fast.ai?
• kanodiaayush 9y ago
  Can we name the links so that we know what each is? @mindcrime
  • mindcrime 9y ago
    I would have but I was half asleep when I first posted that. Luckily someone else came along and labeled them in a reply. :-)
• zengid 9y ago
  I'll add another vote for course.fast.ai since I'm currently working through it. The instructors are serious about delivering a practical course that will get you right into the process of training and playing around with the code. Also, one of the best parts of their courses (they're offering a few simultaneously) is the community of learners that hang around on the forums.
• f00_ 9y ago
  getting your feet wet andrew ng's machine learning course: https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning to get up to date on convnet architecture Fei-Fei Li and Karpathy's cs231n: https://cs231n.github.io/ https://cs231n.github.io/ if you want to go deep geoff hinton's neural networks for machine learning coursera: https://www.coursera.org/learn/neural-networks https://www.coursera.org/learn/neural-networks
• rwieruch 9y ago
  Just recently I have written a "Machine Learning for Web Developers in JavaScript" blog post [0]. If you are a web developer, it might be interesting for you. It outlines my approach of learning it and gives a couple of great resources for JavaScript enthusiasts. Otherwise, I will just post a couple of the materials I used below. It's not only video courses, because I believe it's always useful to stimulate all senses. - [0] https://www.robinwieruch.de/machine-learning-javascript-web-developers/ https://www.robinwieruch.de/machine-learning-javascript-web-... Podcast: - http://ocdevel.com/podcasts/machine-learning http://ocdevel.com/podcasts/machine-learning Courses: - https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning - https://de.udacity.com/course/machine-learning-engineer-nanodegree--nd009 https://de.udacity.com/course/machine-learning-engineer-nano... - https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning - http://course.fast.ai/ http://course.fast.ai/ Books: - https://www.amazon.com/gp/product/B014X01SS0/ https://www.amazon.com/gp/product/B014X01SS0/ - http://www.deeplearningbook.org/ http://www.deeplearningbook.org/ - http://neuralnetworksanddeeplearning.com/ http://neuralnetworksanddeeplearning.com/ - https://www.safaribooksonline.com/library/view/deep-learning/9781491924570/ https://www.safaribooksonline.com/library/view/deep-learning... Math: - http://www.fast.ai/2017/07/17/num-lin-alg/ http://www.fast.ai/2017/07/17/num-lin-alg/ - https://www.khanacademy.org/math/linear-algebra https://www.khanacademy.org/math/linear-algebra - https://www.khanacademy.org/math/statistics-probability https://www.khanacademy.org/math/statistics-probability - https://www.khanacademy.org/math/calculus-home https://www.khanacademy.org/math/calculus-home JavaScript ML: - https://bri.im/ https://bri.im/ - https://github.com/javascript-machine-learning https://github.com/javascript-machine-learning
• Lausbert 9y ago
  A pretty short introduction to machine learning created by myself: http://lausbert.com/2018/01/14/the-shortest-introduction-to-machine-learning/ http://lausbert.com/2018/01/14/the-shortest-introduction-to-...
• dnl_pozzobon 9y ago
  How about Microsoft's AI School https://aischool.microsoft.com https://aischool.microsoft.com