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  1. Advice for Applying Machine Learning, Debugging Reinforcement Learning (RL) Algorithm, Linear Quadratic Regularization (LQR), Differential Dynamic Programming (DDP), Kalman Filter & Linear Quadratic Gaussian (LQG), Predict/update Steps of Kalman Filter, Linear Quadratic Gaussian (LQG)

  2. Perry addresses the fact that an analytical way of thinking and approaching problems from his advanced degree in mathematics was a huge asset for his role as the Secretary of Defense. He stresses that the logic of going through the steps of problem solving will help one build objective decisions about the problem.

  3. Everything at Google has turned out perfectly, making it hard to determine which decisions were good and which were bad. Co-founder Larry Page remarks that they could have started the company earlier, but were working on their PhD's.  Also, it would have been difficult to achieve the same thing five years ago because the market was not as advanced -- and technology was more expensive and less established.

  4. Bartz passion for programming is not about making money; it is about loving what she is doing. Whatever it is your doing, she says, make sure it is something you enjoy. The best leaders who are entrepreneurs are doing what they like.

  5. Transitioning from Sequential Programming to Concurrent Programming in the Ticket Sale Example, Problems with the Sequential Model, Threading Interface, Rewriting the Ticket Example to Use It, Adding a Randomized Threadsleep Call to the Threads to Make the Time Slices Used by the Different Threads Less Uniform, Sample Output of Our Ticket Threads, How a Thread Can be Interrupted in the Middle of a Nonatomic Operation, How Multithreading Ca...more

  6. May 16, 2008 lecture by Rob Miller for the Stanford University Human Computer Interaction Seminar (CS547). Rob Miller discusses some of the explorations into keyword programming in the web automation domain, and also in other domains such as Java development. One surprising result is that programming language syntax often has relatively little information content, and can be inferred automatically from only a handful of keywords -- allowi...more

  7. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Pythonprogramming language.