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Posted by Miguel Vilá
Mon, Nov 20, 2017

In the previous posts, we saw an approach to solving problems in a bottom-up fashion and trying to be functional. In this last post we will see a functional approach when solving them top-down.

Posted by Miguel Vilá
Thu, Oct 12, 2017

In the previous post we saw a way to functionally solve the knapsack problem. Can we do the same when the dependencies between solutions have another shape?

Posted by Miguel Vilá
Wed, Oct 4, 2017

In the last post we saw an imperative solution to the knapsack problem. In this post we will see an initial approach for doing the same thing functionally.

Posted by Miguel Vilá
Mon, Sep 11, 2017

Dynamic programming (DP) is a technique used to solve innately inefficient recursive problems by storing solutions to pre-computed subproblems. The idea is to break a problem into smaller subproblems and save the result of each subproblem so that it is only calculated once. Dynamic programming involves two parts: restating the problem in terms of overlapping subproblems and saving the solution of the subproblems so that we can build the solution to the bigger problem.

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