Bayesian Inference
Understanding posterior distributions, likelihood functions, and priors. Includes Python implementation examples.
A curated collection of notes from my Data Science curriculum. Covering Mathematics, Statistics, Python, and ML algorithms.
Understanding posterior distributions, likelihood functions, and priors. Includes Python implementation examples.
Deep dive into Classes, Inheritance, Polymorphism, and Encapsulation in Python.
Visualizing linear transformations and calculating determinants for dimensionality reduction.
Optimization algorithms visualized. Stochastic vs Batch gradient descent performance comparison.
Implementing raycast logic in Unity C# for projectile collision detection and line-of-sight.
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