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Ask HN: What are some good Machine Learning resources?
I'm currently learning and researching more in the field of Machine Learning. I started with Machine Learning course in Coursera (http://ml-class.org/).
Any other/more suggestions to go deep into the topic?
- deleted 11y ago[deleted]
- adorable 11y agoFor a weekly collection of ML related news and resources, you may want to look at https://aiweekly.curated.co https://aiweekly.curated.co
- yedhukrishnan 11y agoThanks! This will help me to stay motivated every time when a mail comes :D
- shogunmike 11y agoSome good books on Machine Learning: Machine Learning: The Art and Science of Algorithms that Make Sense of Data (Flach): http://www.amazon.com/Machine-Learning-Science-Algorithms-Sense/dp/1107422221/ http://www.amazon.com/Machine-Learning-Science-Algorithms-Se... Machine Learning: A Probabilistic Perspective (Murphy): http://www.amazon.com/Machine-Learning-Probabilistic-Perspective-Computation/dp/0262018020/ http://www.amazon.com/Machine-Learning-Probabilistic-Perspec... Pattern Recognition and Machine Learning (Bishop): http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738/ http://www.amazon.com/Pattern-Recognition-Learning-Informati... There are some great resources/books for Bayesian statistics and graphical models. I've listed them in (approximate) order of increasing difficulty/mathematical complexity: Think Bayes (Downey): http://www.amazon.com/Think-Bayes-Allen-B-Downey/dp/1449370780/ http://www.amazon.com/Think-Bayes-Allen-B-Downey/dp/14493707... Bayesian Methods for Hackers (Davidson-Pilon et al): https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers https://github.com/CamDavidsonPilon/Probabilistic-Programmin... Doing Bayesian Data Analysis (Kruschke), aka "the puppy book": http://www.amazon.com/Doing-Bayesian-Data-Analysis-Second/dp/0124058884/ http://www.amazon.com/Doing-Bayesian-Data-Analysis-Second/dp... Bayesian Data Analysis (Gellman): http://www.amazon.com/Bayesian-Analysis-Chapman-Statistical-Science/dp/1439840954/ http://www.amazon.com/Bayesian-Analysis-Chapman-Statistical-... Bayesian Reasoning and Machine Learning (Barber): http://www.amazon.com/Bayesian-Reasoning-Machine-Learning-Barber/dp/0521518148/ http://www.amazon.com/Bayesian-Reasoning-Machine-Learning-Ba... Probabilistic Graphical Models (Koller et al): https://www.coursera.org/course/pgm https://www.coursera.org/course/pgm http://www.amazon.com/Probabilistic-Graphical-Models-Principles-Computation/dp/0262013193/ http://www.amazon.com/Probabilistic-Graphical-Models-Princip... If you want a more mathematical/statistical take on Machine Learning, then the two books by Hastie/Tibshirani et al are definitely worth a read (plus, they're free to download from the authors' websites!): Introduction to Statistical Learning: http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/ The Elements of Statistical Learning: http://statweb.stanford.edu/~tibs/ElemStatLearn/ http://statweb.stanford.edu/~tibs/ElemStatLearn/ Obviously there is the whole field of "deep learning" as well! A good place to start is with: http://deeplearning.net/ http://deeplearning.net/
- alexcasalboni 11y agoThose are great resources! In case you are interested in MLaaS (Machine Learning as a Service), you can check these as well: Amazon Machine Learning: http://aws.amazon.com/machine-learning/ http://aws.amazon.com/machine-learning/ (my review here: http://cloudacademy.com/blog/aws-machine-learning/ http://cloudacademy.com/blog/aws-machine-learning/) Azure Machine Learning: http://azure.microsoft.com/en-us/services/machine-learning/ http://azure.microsoft.com/en-us/services/machine-learning/ (my review here: http://cloudacademy.com/blog/azure-machine-learning/ http://cloudacademy.com/blog/azure-machine-learning/) Google Prediction API: https://cloud.google.com/prediction/ https://cloud.google.com/prediction/ BigML: https://bigml.com/ https://bigml.com/ Prediction.io: https://prediction.io/ https://prediction.io/ OpenML: http://openml.org/ http://openml.org/
- yedhukrishnan 11y agoI went through the links and your review. They are really good. Thanks!
- yedhukrishnan 11y agoThose are really useful. Thank you. Books are pricey though!
- shogunmike 11y agoI know...some of them are indeed expensive! At least the latter two ("ISL" and "ESL") are free to download though.
- anacleto 11y agoSome great resources just mentioned here. If you're interested in Machine Learning and Cloud then you should definitely try AWS ML and Azure ML. "Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology.” "Azure Machine Learning: a cloud-based predictive analytics service." Here two great tutorials (with code) on Amazon ML and Azure ML. Amazon Machine Learning: use cases and a real example in Python http://cloudacademy.com/blog/aws-machine-learning/ http://cloudacademy.com/blog/aws-machine-learning/ Azure Machine Learning: simplified predictive analytics http://cloudacademy.com/blog/azure-machine-learning/ http://cloudacademy.com/blog/azure-machine-learning/
- yedhukrishnan 11y agoThanks! I'll try these out. Can they be used for learning? I feel it's more like services.
- tacticiankerala 11y agoCheckout, https://github.com/josephmisiti/awesome-machine-learning https://github.com/josephmisiti/awesome-machine-learning This is not exactly resources for learning machine learning but frameworks you can use with your favorite programming language.
- yedhukrishnan 11y agoThat's good. Thanks!
- mark_l_watson 11y agoI would concentrate on just Andrew Ng's course until you finished it. Even though the problem sets are solved using Matlab/Octave you will learn just about all the theory you need to later try different frameworks written in different languages. I earned a 99.6% grade in that class (I have a few decades of AI experience, so I took the class as an excellent review) and I feel that every minute spent on this class was worthwhile.
- yedhukrishnan 11y agoThanks for the advice. Right now, I am concentrating only on the course. I just wanted to keep some resources for later. I'll keep this in mind.
- rayalez 11y agoHere's my list of suggestions: http://digitalmind.io/post/deep-learning http://digitalmind.io/post/deep-learning
- yedhukrishnan 11y agoThat's great! Thanks.. Is that your own blog?
- rayalez 11y agoYep =)