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Dynamic programming is the process of breaking down a larger problem into smaller problems. By using the answers to those smaller problems, we can find the overall solution more efficiently.
We'll also learn about the term "memoization," and how it relates to dynamic programming.
TCP (Transmission Control Protocol) is a protocol for machines to communicate over a network, and is the foundation on which the internet is built.
One of the most useful characteristics of TCP is that it is 'resilient', which means it can cope with an unreliable network without losing any data.
We use these data structures every day in programming.
Even if you're already familiar with them, it's helpful to recap them occasionally.
String similarity metrics have various uses; from user-facing search functionality, to spell checkers.
There are a few common string similarity metrics. Knowing a little about each will help you to choose the right one, should you ever need to implement something like this yourself.
A lot of algorithms are implemented for you as part of your chosen language. That means that they are interesting to learn about, but you'll rarely write them yourself.
Graph traversal algorithms are different. We use graphs all the time, from linking related products in an e-commerce application to mapping relationships between people in a social network.
Bubble sort is an excellent introduction to sorting algorithms.
It is also useful as a reference when we cover more complex search algorithms later.
Have you ever wanted to know:
Imagine we want to store a list of users so that we can find them later using their names.
Why should I care?
There are many real-life problems that are very similar to the Travelling Salesman Problem.
Have you ever wanted to know:
Suppose we want to compress a string (Huffman coding can be used with any data, but strings make good examples).