DataForScience/Probability
Applied Probability Theory for Everyone
This resource helps you understand and apply probability theory to real-world scenarios, even if you don't have a strong math background. It provides hands-on code and explanations that take you from basic concepts like calculating probabilities to advanced topics like Bayesian analysis and A/B testing. Anyone looking to build a practical foundation in probability for data analysis, decision-making, or scientific research will find this useful.
124 stars. No commits in the last 6 months.
Use this if you need to grasp core probabilistic concepts and their practical applications, like understanding A/B test results or modeling sequences of events.
Not ideal if you are looking for an advanced academic textbook on measure theory or highly theoretical probability proofs without practical coding examples.
Stars
124
Forks
55
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 29, 2024
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