September 2018
Intermediate to advanced
288 pages
7h 38m
English
book
Keras Reinforcement Learning Projects
by Giuseppe Ciaburro, Sudharsan Ravichandiran, Suriyadeepan Ramamoorthy
Content preview from Keras Reinforcement Learning Projects
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Summary
In this chapter, we have addressed the basic concepts of the optimization techniques. To start, we learned the essential contents underlying the DP. With DP, we subdivide an optimization problem into simpler subproblems. We then proceed to calculate the solutions of all possible subproblems, and starting from subsolutions, we obtain new subsolutions, and carry on until we solve the original problem.
Then, we looked at the difference between recursion and memoization. In DP, this does not happen: we memorize the solution of these subproblems so that we do not have to solve them again; this is called memoization. The idea behind this method is to calculate solutions to subproblems once and store the solutions in a table so that they ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.