Ask HN: What are some good Machine Learning resources?

https://news.ycombinator.com/item?id=9530407

by yedhukrishnan • 11 years ago

17 16 11 years ago

news.ycombinator.com

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?

adorable• 11 years ago

For a weekly collection of ML related news and resources, you may want to look at https://aiweekly.curated.co

yedhukrishnan7• 11 years ago

Thanks! This will help me to stay motivated every time when a mail comes :D

shogunmike2• 11 years ago

Some 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-Se...

Machine Learning: A Probabilistic Perspective (Murphy): http://www.amazon.com/Machine-Learning-Probabilistic-Perspec...

Pattern Recognition and Machine Learning (Bishop): 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/14493707...

Bayesian Methods for Hackers (Davidson-Pilon et al): 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...

Bayesian Data Analysis (Gellman): http://www.amazon.com/Bayesian-Analysis-Chapman-Statistical-...

Bayesian Reasoning and Machine Learning (Barber): http://www.amazon.com/Bayesian-Reasoning-Machine-Learning-Ba...

Probabilistic Graphical Models (Koller et al): https://www.coursera.org/course/pgm 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/

The Elements of Statistical Learning: 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/

alexcasalboni• 11 years ago

Those 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/ (my review here: http://cloudacademy.com/blog/aws-machine-learning/)

Azure Machine Learning: http://azure.microsoft.com/en-us/services/machine-learning/ (my review here: http://cloudacademy.com/blog/azure-machine-learning/)

Google Prediction API: https://cloud.google.com/prediction/

BigML: https://bigml.com/

Prediction.io: https://prediction.io/

OpenML: http://openml.org/

yedhukrishnan7• 11 years ago

I went through the links and your review. They are really good. Thanks!

yedhukrishnan7• 11 years ago

Those are really useful. Thank you. Books are pricey though!

shogunmike2• 11 years ago

I know...some of them are indeed expensive!

At least the latter two ("ISL" and "ESL") are free to download though.

anacleto• 11 years ago

Some 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/

Azure Machine Learning: simplified predictive analytics http://cloudacademy.com/blog/azure-machine-learning/

yedhukrishnan7• 11 years ago

Thanks! I'll try these out. Can they be used for learning? I feel it's more like services.

tacticiankerala• 11 years ago

Checkout, 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.

yedhukrishnan7• 11 years ago

That's good. Thanks!

mark_l_watson• 11 years ago

I 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.

yedhukrishnan7• 11 years ago

Thanks 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.

rayalez2• 11 years ago

Here's my list of suggestions:

http://digitalmind.io/post/deep-learning

yedhukrishnan7• 11 years ago

That's great! Thanks.. Is that your own blog?

rayalez2• 11 years ago

Yep =)

Ask HN: What are some good Machine Learning resources?

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