We've been busy

but now it's time to post again!

+

=

if you haven't seen it yet, we do recommend

There is a new release of Deep Learning Book by Yoshua Bengio: http://www.iro.umontreal.ca/~bengioy/dlbook/

Do not hesitate to forward these messages to fellow data scientists

In this notebook, we cover the basics of probability theory, and show how to implement the theory in Python. (You should have a little background in probability and Python.) Then we show how to solve some particularly perplexing paradoxical probability problems.

http://vk.com/wall-103600381_5

Hakathon from russian Facebook

The essential mathematics necessary for Data Science can be acquired with these 15 MOOCs, with a strong emphasis on applied algebra & statistics.
http://www.kdnuggets.com/2015/09/15-math-mooc-data-science.html

for whom it may concern
http://insightdatascience.com

"On the ImageNet dataset, our method reduced the storage required by AlexNet by 35x from 240MB to 6.9MB, without loss of accuracy. Our method reduced the size of VGG16 by 49x from 552MB to 11.3MB, again with no loss of accuracy."