This project contains solutions to problems from Project Euler. The solutions are implemented in Python and are intended to demonstrate the following concepts and skills:
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Algorithmic Thinking: Many of the problems require the design of efficient algorithms.
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Mathematical Knowledge: The problems often involve concepts from number theory, combinatorics, probability, and other branches of mathematics.
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Programming Techniques: Various programming techniques and data structures are used to solve the problems efficiently. This includes techniques like dynamic programming, graph algorithms, and efficient use of data structures like arrays, lists, sets, and dictionaries.
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Performance Considerations: The problems often involve large inputs, requiring code that is not just correct, but also fast. This involves thinking about the time and space complexity of the code, and making trade-offs between the two.
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Precision and Accuracy: Some problems involve calculations with real numbers, where precision can be an issue. This can teach about the limitations of numerical computation and how to handle them.
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Code Optimization: As the problems get more complex, brute force solutions become less feasible. This encourages learning and applying optimization techniques to make the code more efficient.
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Language Features: Different programming languages have different strengths and weaknesses. Some problems might be easier to solve in one language than another. In this project, we use Python and explore its strengths and weaknesses in solving these problems.
Each notebook in the project contains the solution to a problem, along with a detailed explanation of the solution approach and any interesting programming or mathematical concepts involved.