This is a Ruby on Rails application that will mine the United States Chess Federation website for data and present it.

When I was a more serious chess player, I would always do things like this for myself. I kept meticulous records of all my games and would keep track of how I did under various circumstances against various people, look at my trends, and try to use them to understand myself better. I reveled in my biggest upsets and best performances while being upset by my worst losses. I compared myself to my friends and rivals using various criteria and invented goals for myself.

I am hoping to apply these same ideas and experiences to build an app that a lot of people can use.

9/22:

-Initiated project
-Learned about Nokogiri and Mechanize via RailsCasts
-Built web scraper to parse the USCF website and get data using regular expressions and CSS selectors
-Create UscfWebsite class to hold common methods for accessing the USCF website

9/23:

-Learned about Ajax in Rails (annoying because a lot changed in Rails 3.1 so all
 the tutorials were outdated)
-Used instance variables in partials with Ajax calls to dynamically update the page using a Ruby object
-Wrote code to collect all the opponents someone has ever played and sort them by rating
-Made MySQL database, pushed project to Heroku, sorted out little bugs in transitioning
-Doing it all in one call caused Heroku to timeout for players with long histories, 
 so I went through and made the entire thing a collection of Ajax calls that pass JSON objects
 and arrays back and forth to collect all the data
-Added some jQuery to make the user interface a little more friendly and show a progress
 indicator with % complete and the date of the last tournament processed

9/24:

-Worked on the Stanford machine learning course

9/25:

-Worked on the Stanford machine learning course

9/26:

-Built a good user interface
-Wrote an intro to the app to show to people

9/27:

-Spent a long time fighting with the poorly-formatted USCF website
-Learned that Ruby regular expressions don't recognize some of the UTF-8 blank space characters

9/28:

-Talked to GoDaddy and learned how to properly redirect naked domains through the Heroku proxy to the main page.
-Put a link to the website on chess.stackexchange.com

9/29:

-Added a bunch of methods to the API
-Did some bug fixing
-Played in a tournament and invited people to visit the website

9/30:

-Redesigned the code for the demo to make it better
-Added a lot of new columns
-Made the user interface a lot better
-Let users choose between regular and quick history
-Put sorting on the columns

10/1:

-Identified problems in the current demo design
-Learned about Redis
-Implemented a Redis NoSQL cloud database and set up the application to work with it
-Rewrote various parts of the application to use the new database
-Fixed some bugs
-Set the type and USCF ID to be session variables

10/2:

-Fixed some small bugs

10/3:

-Worked on the Stanford machine learning course

10/4:

-Went to hack night with the Research Triangle Ruby meetup group
-Built the get_results_against_opponents_from_tournament method in the USCF Website API

10/5:

-Vacation to visit my father, didn't work on stuff

10/6:

-Still on vacation
-Poked at the FANN neural network library

10/7:

-Still on vacation
-Learned some D3JS
-Built draft of delta chart

10/8:

-Worked on learning D3JS

10/9:

-Added D3Js axis to delta chart
-Did some math to scale the locations and sizes of the axis and bubbles according to the specified width/height.
-Made the bubbles say who you played
-Updated the interface to make it a little better and let users input the ID of who to check out

10/10:

-Usability testing, someone noticed a major bug in the deltas chart in later versions of Firefox.
-Opened issue, found solution and fixed it.

10/11:

-Busy watching the debate

10/12:

-Busy doing other things

10/13:

-Did some research and discovered locally weighted logistic regression
-Read Ph.D thesis paper and tried to implement a library for the algorithm in Ruby
-Got irritated with poorly written paper
-Made the deltas example a collection of AJAX calls similar to the demo example
-UI/UX changes to the deltas example

10/14:

-Fixed a defect in the deltas page
-UI/UX changes to deltas page
-Looked up the mathematical papers behind the USCF rating system to get a better understanding of it
-Opened up the JavaScript for the performance calculator on the USCF website and read it
-Implemented a binary search algorithm similar to that on the USCF website in Ruby to calculate performances
-Learned how to do line charts in D3JS
-Learned how to do time scales in D3JS
-Built a line chart that shows performance ratings and regular ratings over time
-Added buttons to deltas and performance charts to add gridlines.

10/15:

-Found out there's a tiny book on D3JS, read about fifty pages of it
-Added some animations and hovers to the charts

10/16:

-Finished D3JS book
-Added cool D3JS things to the charts
-Better hovers on the performance chart

10/17:

-Made the performance chart example a collection of AJAX calls
-Used D3JS's algorithms to make a force-directed graph to represent the results of a tournament

10/18:

-Busy doing other things

10/19:

-Busy doing other things

10/20:

-Studied linear regression
-Built a structure to add a linear regression model to the performance chart using the normal equation
-Let users choose features
-Users can choose arbitrary data and use machine learning to get an expected performance

10/21:

-Fixed a bug, did some testing

10/22:

-Added a new method to the USCFWebsite class to count how many games someone played in a tournament
-Started building a chart to show rating/performance vs number of games played
-The USCF has blocked my localhost from accessing their website, so I'll have to develop from a VPN from now on.

10/23:

-Made some cosmetic changes

10/24:

-Made some more cosmetic changes
-Updating routing a bit

10/25 - 11/29:

-Took a month-long break
-Studied public speaking and developed foreign policy ideas for the U. Penn Model U.N. conference
-Visited Amelia in Massachusetts

11/30:

-Built a logistic regression class that implements a basic logistic regression algorithm.
-Added two logistic regression classifiers to the deltas page
-Predict what rating difference marks the point where a player has a better chance of winning/drawing by rating.

12/1:

-Built a linear regression class to implement a basic linear regression algorithm
-Added two linear regression lines, with features log(rating) and log^2(rating), to the performances page.
-Made various parts of the website work better and look better.

12/2:

-Found a problem with the logistic regression classifier.
-Spent a while exploring various solutions, couldn't find a consistent one, asked a question on StackOverflow.
-Made a lot of cosmetic changes to the site.

12/3:

-Updated what the description says on the homepage.