Machine Learning and AI Study Repo 🤖

Hey there! This is my study repository as I go through the book "Machine Learning: A Probabilistic Perspective." The goal is to understand machine learning and AI algorithms better by coding them up.

What's Inside 📦

• Notes: Summaries and key points from each chapter in Markdown format.
• Distributions: Code examples of different probability distributions.
  • Written in C++ and maybe some Python.
• Algorithms: Implementations of ML algorithms like KNN.
  • Primarily in C++ and maybe Python.
• Models: Implementations of statistical models like Naive Bayes.
  • Also in C++ and possibly Python.

File Structure 🗂

.
├── Notes
│   └── Chapter_1.md
│   └── Chapter_2.md
│   └── ...
├── Distributions
│   ├── Gaussian
│   │   ├── main.cpp
│   │   └── README.md
│   ├── ...
├── Algorithms
│   ├── KNN
│   │   ├── main.cpp
│   │   └── README.md
│   ├── ...
└── Models
    ├── Naive_Bayes
    │   ├── main.cpp
    │   └── README.md
    ├── ...