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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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I spent a lot of the past year preparing for and taking technical interviews. This meant a lot of Data Structures, Algorithms, Graphs, Counting, and a whole lot of general Leetcoding.
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NBA stats and analytics are growing as a field and becoming more and more popular among young programmers seeking entry into fields of data analysis, machine learning, and general statistics.
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The goal of this project was to capture the recent sentiments from r/nba about NBA players and teams. After capturing relevant data, we want to display it in a visually appealing fashion and convey details about why a certain team or player got the score.
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When attempting to achieve a performant solution to a problem that seems fairly brute-forcey, we often turn to dynamic programming. But DP necessecitates us to maintain some sort of state in order efficiently cache intermediate solutions.
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I ran into a similar pattern Leetcode problem over the past 3 days and decided it was a common enough pattern that I should make a post about it.
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The sliding window is a common technique used to solve questions relating to continuous substrings or subarrays.
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Behavioral interviews are tricky. They aren’t as straightforward as technical interviews and some people simply aren’t too good at them. The main differences are:
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A cool interview question I was asked for a frontend role recently was: