waitingkuo

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this remind me ruby...

It's opened and free now https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8...

I always think that learning probability can not only help you to gain more intuition when dealing with scientific relative subjects but also empower you to think the daily life things in a different way. I recommend Introduction of probability [1] since it's easy to study and provides great free video lectures [2].

[1] - https://www.amazon.com/Introduction-Probability-Dimitri-P-Be...

[2] - https://ocw.mit.edu/resources/res-6-012-introduction-to-prob...

This is amazing work. Look forward to the integration between go & python

Will Grumpy be a good fit for go's scientific packages such like gonum?

You need a GSM Core Network[1]. For more details, you can take a look at HLR and AuC components which are responsible for authentication.

[1] https://en.wikipedia.org/wiki/Network_switching_subsystem#Au...

Most of them are about Data Science / Machine Learning and some math stuff

Disclaimer: I've paid for many courses but never paid for a specialiazation.

I personally don't care about the effect of the certificate. I paid simply because what instructor taught me worth more than it cost.

Does this work in China? We're considering giving it a try but the biggest concern is that one of our office is located in China.

In my experience, the best part of Meteor is its tightly couple stack so that I can developer very smoothly. But the worst part is also its tightly couple stack when my web/app grows. Really hope that it would be easier to decouple some important package like tracker or minimongo

As always! It need a http://www.netflix.cn/ first

It's definitely a huge contribution. But P=NP potentially means that RSA is solvable in Polynomial time. Then countless servers will be attackable. Not sure whether it's good to announce "publicly".

I've tried to learn R several time, but its index started with 1 always stop me from learning.

Author here. We first crawl some pages and then used sentimental analysis like process to analyze these pages. Instead of sentiment dictionary, we built our own Branding dictionary. The result (radar chart and the bar chart) is based on the text used in the site. Thank you for the interest.

The Udacity one (introduction to Machine Learning) is very practical in my mind. It only description some intuition and then show you how to call scikit-learn's function to do some simple machine learning works.

Believe or not, telnet://ptt.cc , one of the bbs in Taiwan, is still highly active with more than 100k concurrent users normally.

Can I run docker on this?