people you shall know as a computer scientist

Bruce R. Land (Senior Lecturer at School of Electrical and Computer Engineering at Cornell University)

• Home page: http://people.ece.cornell.edu/land/
• Online Lecture (Sample): https://www.youtube.com/watch?v=_P2w-RiCo1U

Robert Sedgewick (Senior Researcher for efficient algorithms, Department of Computer Science at Princeton University)

• Home page: https://www.cs.princeton.edu/~rs/
• Online Lecture (Sample): https://www.coursera.org/learn/algorithms-part1

norm

A very well written definition of norm can be found:

• https://rorasa.wordpress.com/2012/05/13/l0-norm-l1-norm-l2-norm-l-infinity-norm/ (thanks Wattanit H. for the good summary)

 

Repository of Sources to learn Data Science

The following Github repository provides a rich set of sources to learn data science:

• https://github.com/bulutyazilim/awesome-datascience

The following Links provides an introduction into backpropagation in python3

• http://python3.codes/neural-network-python-part-1-sigmoid-function-gradient-descent-backpropagation/

 

Online Distribution Calculator

This is a link to an online distribution calculator, you can get the percentile of a particular x value for a chosen distribution function.

https://gallery.shinyapps.io/dist_calc/

Handle return in ES6 lambda expression

More details about how to handle the implicit and explicit can be found in the follow URL: http://stackoverflow.com/questions/28889450/when-should-i-use-return-in-es6-arrow-functions