Continuing Education & Solution Manuals

 

 

Online Courses

The web is a great place to expand ones knowledge base. I've tried to keep abreast of interesting technical things by taking online classes from time to time using platforms like coursera. The classes I have taken include:

The Stanford University class Algorithms I which you can read more about here. You can find my statement of accomplishment here.

University of Minnesota class Introduction to Recommender Systems which you can read more about here. You can see a screen shot of my class progress here.

Stanford University class entitled Mining Massive Datasets which you can read more about here. You can find my statement of accomplishment here.

Stanford University class on Statistical Learning which you can read more about here. You can find my statement of accomplishment here.

The online Stanford class on probabilistic graphical models which you can read more about here. This involved a massive amount of work but I don't know of any other way to get such an introduction to this material. In all likelihood Bayesian networks will become the standard techniques for performing reasoning under uncertainty. My statement of accomplishment in the class can be found here.

The online Stanford AI class which you can read more about here. This was a nice way to get a quick introduction to some AI topics. My statement of accomplishment in the class can be found here.

The Columbia University course Financial Engineering and Risk Management which is now split into two classes. The first is here. You can find my statement of accomplishment for the original version here.

The University of Toronto's class Neural Networks for Machine Learning which you can read more about here. You can find my statement of accomplishment here.

Stanford University class on Machine Learning which you can read more about here. You can find my statement of accomplishment here.

Worked Problems, Solution Manuals & Notes from Various Books

Here are some notes and problem solutions from a sample of the books I have studied from. I decided to put this material on-line because at some point I'd like to turn as many of these very informal "notes" into full fledged solution manuals. Currently, I am working on the solution manual for A First Course in Probability by Sheldon Ross.

This work was done for improving my own understanding of the material and I can't claim that every detail has been worked to completion. Often on a given problem or derivation when I felt I understood the rest of the required manipulations I would simply stop working.

Mathematical material is not always easy and it would be a lie to say that all of my attempts have been met with success. I have tried to work everything as correctly as possible and believe that many of the things I place here are correct, but I am only human and know some subjects much better than others. Please report any errors that you may find and I'll work to incorporate these into new versions (with credit of course). As a legal disclaimer: I can take no responsibility for any loss or damage that may be caused by using any of the notes placed here.

Finally, if anyone is looking for some practice with LaTeX I would be ecstatic to obtain even the smallest amount of LaTeX translations for any of the scanned (hand-written) notes. More information on LaTeX can be found here.
View Comprehensive List of Problems, Manuals and Notes


Current Reading

In addition to the books I have finished, I keep a list of the books I am currently working on.
 Download a PDF of Current Reading


Additional Study / Books Read

I try to read as much technical material as I have time for. As such, I have read a reasonable number of books on a large number of different topics. Below you will find a partial list of books/documents I have read since I started keeping track. I try to read books very thoroughly, working as many problems as I have time, in hopes of really mastering the material.
 Download a PDF of Books Read