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{
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  "name": "hw3-solutions-1-and-2"
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{
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{
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Introducing Fernando

It is my pleasure today to introduce Fernando Perez, a research scientist at UC Berkeley.

Bill Punch suggested I introduce Fernando by asking, what is a swiss army knife for?  The answer is that it's an inexpensive, versatile, and extremely effective tool that contains lots of tools, most of which you don't use or have any idea of what they are.  However, it's safe to say that if you got dropped off on a desert island, a swiss army knife would be one of your most important tools for survival.

Fernando is the lead developer of the ipython project, which is the swiss army knife of scientific computing.  It's an incredibly widely used free, open source, tool for working with data and code; but, because it's neither sexy or nor well funded, it's not on the radar.  It's "just" widely used, and I routinely find that it has already solved problems five years ahead of when I've had them.

Fernando will be talking about the ipython notebook, which is a transformative solution reproducible resea

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Title: Implementing Awesome Big Data Algorithms Effectively

C. Titus Brown* and Eric McDonald

Random algorithms and probabilistic data structures are algorithmically
efficient and can provide shockingly good practical results.  I will briefly
cover a few commonly used probabilistic data structures, then describe their
implementation in Cython and C++.  The bulk of the talk will be spent 
discussing performance considerations of implementations, including caching and 
approaches to threadsafety.  This will be a in-depth extension of my "Awesome

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Version control for scientific research

We live in an increasingly collaborative era, where the Internet enables distance collaboration almost trivially -- not just with e-mail and videoconferencing, but with collaborative realtime document editing and networked transmission of data and analyses. These tools allow us to collectively leverage many resources to rapidly solve problems and ultimately accelerate scientific discovery. But while these tools and technologies are fundamentally changing how we collaborate on science, there is still considerable room for