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Although, there is no denying that this is a valuable resource but I have started to get turned off by a list of n books to learn something - they can be valuable but it is undeniable that they can also be overwhelming and perplex someone about how to get started. I believe technical books should be used to complement your knowledge of the field not to get started in it. For eg, "Secrets of the JavaScript Ninja" will…
Honest question: is ML/DS something you can just pick up and be hired[0]? May be I'm ignorant, but I'd think employers would look for a degree in some related field to actually consider you for a position doing it. [0] As in how you can pick up web hacking, do a few websites and create a reputation and get hired that way without a formal degree.
Any specific recommendations from anyone?
The Elements of Statistical Learning together with the online course ( http://www.r-bloggers.com/in-depth-introduction-to-machine-l... ) makes for a great introduction. EDIT: Oops I should have said "An Introduction to Statistical Learning with Applications in R" rather than The Elements of Statistical Learning. The Elements book goes into way too much depth to be a good introduction to the subject.
While this is no doubt really interesting, I find I am getting diminishing returns from outputting stats like this from big dumps of past historical data. What I would like to be able to show is a live heat graph style stats tracker, where each point in the match updates my belief net about who is winning, or playing better. Of course, the final outcome may be upended by some fluke occurrence such as a Hail Mary pass in the final seconds which is what makes sports interesting, but nonetheless I think a live tracker would say a lot more than the actual score of the match.
So, I am wondering if anyone has specific resources for real time online data mining? At web scale for high throughput data streams. And I agree with shubmajain above, libraries and repos are preferable to books and academic journals ;)
I would add these great ebooks on Cloud Computing and AWS Certifications:
The Cloud Computing Job Market
With this eBook you will learn how Cloud Computing is changing the IT industry and creating a complete set of new roles for companies and businesses worldwide. Information and data to start your cloud computing career.
Link [0] https://cloudacademy.com/ebooks/cloud-computing-job-market-3...
A Guide to AWS Certification Exams
Introduction to the full range of Amazon Web Services certification exams: learn what, why, and how to pass just the right exam for you.
Link [1] https://cloudacademy.com/ebooks/guide-aws-certification-exam...
AWS Solutions Architect Certification
Study guide to Amazon Web Service's Solutions Architect certification exam: tips and suggestions on how, what, and where to learn.
Link [2] https://cloudacademy.com/ebooks/aws-solutions-architect-cert...
Earlier quoted context omitted.
The Elements of Statistical Learning together with the online course ( http://www.r-bloggers.com/in-depth-introduction-to-machine-l... ) makes for a great introduction. EDIT: Oops I should have said "An Introduction to Statistical Learning with Applications in R" rather than The Elements of Statistical Learning. The Elements book goes into way too much depth to be a good introduction to the subject.
Similarly, An Introduction to Statistical Learning With Applications in R is like a practical version of (or companion to) Elements. I very much enjoyed it.
https://lagunita.stanford.edu/courses/HumanitiesandScience/S...
Honest question: is ML/DS something you can just pick up and be hired[0]? May be I'm ignorant, but I'd think employers would look for a degree in some related field to actually consider you for a position doing it. [0] As in how you can pick up web hacking, do a few websites and create a reputation and get hired that way without a formal degree.
Anyone recommend any of the R books listed or know of any great R books for purchase?
I really enjoyed the book, it took a modern approach to R using many of the newer packages (dplyr for instance) and ggplot and combined them into a very nice introduction to R with labs, etc. Well worth checking out.