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Activity timeline

November 2, 2009

Chapter 3 covered quite a lot it felt like, including the fact that Amazon's S3 is a RESTful service, is quite simple and elegant, and was the main example. This chapter also assumed knowledge of Ruby on Rails when it made analogies between S3 and ActiveRecord, but the main points were clear. I was pleased to see some Python code, even if it was a client talking to a RESTful service written using ActiveResource. Oh, and 'whytheluckystiff' wrote a S3 clone called ParkPlace for hosting your own S3 service!

November 1, 2009

Chapter 1 introduces the ideas behind REST and a taxonomy of other web services that aren't exactly REST. This seems like a great start — I now know what differentiates true RESTful APIs and things like SOAP.

June 15, 2009

Chapter 4. URLs and Views. This chapter was pretty short and sweet, providing some fun examples, like wrapping views to achieve a dual-format for both AJAX calls and normal HTML requests, and object-based views.

Chapter 3: Models. I skimmed a lot of this chapter since it dealt with some of the internals of the ORM that I don't usually delve into. Hopefully the little bit I might remember will remind me to re-visit this chapter when I need to dive into models.

March 6, 2009

Chapter 5, Let's Obtain the Probability, covered Normal Distribution, Chi Square, and T and F distribution very briefly. It seemed a bit loose on the details but maybe this book is intended more as a high level overview than a down and dirty math statistics book. Either way, I'm learning some things in a new and interesting format.

February 12, 2009

Chapter 4, Standard Score and Deviation Score, is back on track with a full chapter. Taken from examples of grading tests on a curve, this chapter explains the statistics of what's going on nicely. And OMG, Cake!

February 11, 2009

Chapter 3, Understanding Categorical Data, was literally only a few pages long and talked about cross tabulating categorical data to get a bigger picture. This chapter seemed odd that it was so short and covered only one point. Weird.

Chapter 2, Understanding Numerical Data, was simple and straightforward about averages, means, and standard deviation, with helpful examples that were walked through. The crush plot line has toned down.

February 10, 2009

Chapter 1, Determining Data Types, made it very easy to understand the difference between categorical and numerical data. So far so good. The story of the little girl with the crush on the statistics teacher is a little cheesy, but it adds some humor and plot to an otherwise boring topic.

January 21, 2009

Chapter 2: Django is Python. The most awesome-est chapter I've read from a technical book. Ever. Seriously. All the great advanced Python tricks that I knew I should know but I've put off learning are covered here, and then some.

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