Learning in an online world

Since I started at Dynamic Controls about two years ago, engineers have done free online courses in machine learning, artificial intelligence, cryptography and digital electronics. These services are just starting to build momentum, have a go at many computer science topics at coursera.org or udacity.com, for something completely different learn a language while transcribing the web at duolingo.com.

The business also promotes internal classes, from topics related to each department like Finance 101 to classes run by enthusiasts in a particular domain like the Chinese language or Programming in Python.

I'm about to embark on teaching the "Introduction to Programming" course for the third time. It is so rewarding to see many of my previous students use Python to automate some repetitive part of their job. Everyone has been happy using Python 3 as their first programming language.

We live in a wonderful world with a rich culture of free learning and education.

Homomorphic encryption using RSA

I recently had cause to briefly look into Homomorphic Encryption , the process of carrying out computations on encrypted data. This technique allows for privacy preserving computation. Fully homomorphic encryption (FHE) allows both addition and multiplication, but is (currently) impractically slow. Partially homomorphic encryption just has to meet one of these criteria and can be much more efficient. An unintended, but well-known, malleability in the common RSA algorithm means that the multiplication of ciphertexts is equal to the multiplication of the original messages. So unpadded RSA is a partially homomorphic encryption system. RSA is beautiful in how simple it is. See wikipedia to see how to generate the public ( e , m ) and private keys ( d , m ). Given a message x it is encrypted with the public keys it to get the ciphertext C ( x ) with: C ( x ) = x e mod m To decrypt a ciphertext C ( x ) one applies the private key: m = C ( x ) d mod m The homomorphic prop...

Matplotlib in Django

The official django tutorial is very good, it stops short of displaying data with matplotlib - which could be very handy for dsp or automated testing. This is an extension to the tutorial. So first you must do the official tutorial! Complete the tutorial (as of writing this up to part 4). Adding an image to a view To start with we will take a static image from the hard drive and display it on the polls index page. Usually if it really is a static image this would be managed by the webserver eg apache. For introduction purposes we will get django to serve the static image. To do this we first need to change the template. Change the template At the moment poll_list.html probably looks something like this: <h1>Django test app - Polls</h1> {% if object_list %} <ul> {% for object in object_list %} <li><a href="/polls/{{object.id}}">{{ object.question }}</a></li> {% endfor %} </ul> {% else %} <p>No polls...

Python and Gmail with IMAP

Today I had to automatically access my Gmail inbox from Python. I needed the ability to get an unread email count, the subjects of those unread emails and then download them. I found a Gmail.py library on sourceforge, but it actually opened the normal gmail webpage and site scraped the info. I wanted something much faster, luckily gmail can now be accessed with both pop and imap. After a tiny amount of research I decided imap was the better albiet slightly more difficult protocol. Enabling imap in gmail is straight forward, it was under labs. The address for gmail's imap server is: imap.gmail.com:993 Python has a library module called imaplib , we will make heavy use of that to access our emails. I'm going to assume that we have already defined two globals - username and password. To connect and login to the gmail server and select the inbox we can do: import imaplib imap_server = imaplib . IMAP4_SSL ( "imap.gmail.com" , 993 ) imap_server . login ( use...

Bits of py

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