gamapuna

Here's a recent interview of Avi Loeb on this subject https://www.youtube.com/watch?v=_DQYiyQ7Tkk

planet earth (both the parts) for me

I use hn.algolia, if there's some topic I am interested in searching there usually fives me the most relevant HN link

This was posted before , but IMO is very well written:- https://www.igvita.com/2014/05/05/minimum-viable-block-chain...

In addition to cs231n which someone recommended, I would also suggest cs224d (stanford) and university of waterloo's course by ali ghodsi STAT 946

check out cs224d and cs231n (both stanford) , there's another course by university of waterloo https://uwaterloo.ca/data-science/deep-learning , you will find lecture videos for all on youtube

Thanks for posting OP, can someone comment on how this compares to mit 6.830 (hopefully someone who has taken both the courses :)) http://db.csail.mit.edu/6.830/sched.html http://db.csail.mit.edu/6.830/notes.html

For folks interested there's another implementation specific db course https://web.stanford.edu/class/cs346/2015/ although the lectures are not on youtube

Slightly off topic but for anyone who is taking this course ...are the materials only related to NLP or are the techniques much more broadly applicable to other areas of deep learning (cursory look of the syllabus suggests this but would be great if someone who is actually taking this course can comment)

A couple of friends recommended these:- (Not sure if they are relevant though for deep learning specifically)

1) http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-... 2) https://www.khanacademy.org/math/linear-algebra/vectors_and_...

If anyone knows anything else (relevant to deep learning) could you please share :)

Folks who have taken this course, can you please share your experience

Can anyone recommend a good scala based open source project which gives a flavor of how to write good/effective scala

I am working my way through Alex Aiken's Coursera compiler course, almost 3/4th done and really liking it till now. There was another resource posted on HN earlier which takes you through building a compiler for lisp using C. http://www.buildyourownlisp.com/contents

http://nil.csail.mit.edu/6.824/2015/schedule.html MIT distributed systems course is pretty good IMO.

https://pdos.csail.mit.edu/6.828/2014/schedule.html The mit website pretty much has all the information open, which you can use to go through this course at your own pace. The lectures(most if not all) are on youtube, search for 6.824

Here's the complete course: http://alex.smola.org/teaching/cmu2013-10-701/

Maybe you are correct, Hbase is not easy to configure for sure but in terms of scalability (sheer number of row keys you can dump) there are not a lot of other components which can compete.

Although theoretically this abstraction can live on top of any backend which has facilities for fast prefix scans.

I agree although,I was not aware of django-haystack at the time :)

The primary motive for writing this was the fact that Hbase gives a fairly cheap(hdfs) backend storage and near linear scalability. Also most of the schema is encoded in row keys in such a way that hbase prefix scans can be leveraged to serve traversals across billions of nodes/edges.