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ProbPy is a comprehensive repository dedicated to providing an extensive collection of probability puzzles, riddles, and solutions typically encountered in data science and quantitative research interviews.

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ProbPy - Probability Riddles and Puzzles

I am working on a project with @LeoPag. You can find more details here. This repository works only as a placeholder for the original one you can find at the link above.

Welcome to ProbPy - a comprehensive repository dedicated to providing an extensive collection of probability puzzles, riddles, and solutions typically encountered in data science and quantitative research interviews.

Description

This GitHub repository is tailored for individuals passionate about problem solving or preparing for interviews in fields such as data science, machine learning, AI, quantitative analysis, and related disciplines. Each puzzle is accompanied by a detailed solution written in LaTeX, for those preferring mathematical clarity, and a Python simulation, for those wanting to visualize and understand the problem practically. Navigate through a plethora of problems enriched with LaTeX solutions and Python simulations. Explore topics from conditional probability, statistical distributions, to Markov chains, and more. Master the art of probabilistic thinking with ProbPy!

The scope of this project includes, but is not limited to, problems related to:

  • Probability theory
  • Random variables and statistical distributions
  • Conditional probability and Bayes' theorem
  • Hypothesis testing
  • Combinatorics and permutations
  • Markov chains and stochastic processes
  • Statistical inference The repository's content is carefully crafted and meticulously organized to facilitate easy navigation and efficient learning.

Share your thoughts, improvements, or requests for specific problems by creating an issue or a pull request. Happy problem-solving!

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ProbPy is a comprehensive repository dedicated to providing an extensive collection of probability puzzles, riddles, and solutions typically encountered in data science and quantitative research interviews.

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