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cp-algorithms.com | ||
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www.oranlooney.com
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| | | | | A common example of recursion is the function to calculate the \(n\)-th Fibonacci number: def naive_fib(n): if n < 2: return n else: return naive_fib(n-1) + naive_fib(n-2) This follows the mathematical definition very closely but it's performance is terrible: roughly \(\mathcal{O}(2^n)\). This is commonly patched up with dynamic programming. Specifically, either the memoization: from functools import lru_cache @lru_cache(100) def memoized_fib(n): if n < 2: return n else: return memoized_fib(n-1) + memoiz... | |
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henrikwarne.com
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| | | | | I recently finished the Coursera course Algorithms: Design and Analysis, Part 2 by Professor Tim Roughgarden of Stanford.I've already reviewed part 1, and here are my thoughts on the second part. The main theme of part 1 was the divide and conquer paradigm. In the second part the main themes were greedy algorithms, dynamic programming... | |
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www.adamconrad.dev
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| | | | | Follow along with Steven Skiena's Fall 2018 algorithm course applied to the JavaScript language. | |
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www.randomservices.org
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| | | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight. | ||
