Machine Learning

Personal notes, notebooks, and projects from self-studying machine learning alongside a Mechanical Engineering degree at UCF. Primary resource is Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow (3rd edition) by Aurélien Géron.

The long-term goal is to apply ML at the intersection of mechanical engineering — things like predictive maintenance, physics-informed neural networks, and simulation optimization.

Structure

machine-learning/
└── Ch2/
    └── test.ipynb    # Chapter 2 — End-to-End ML Project (California Housing)

Progress

Chapter	Topic	Status
1	The Machine Learning Landscape	✅ Done
2	End-to-End ML Project	🔄 In Progress
3	Classification	⏳ Upcoming
4	Training Models	⏳ Upcoming
5	Support Vector Machines	⏳ Upcoming

Tools & Libraries

• Python 3
• Jupyter Notebooks
• NumPy, Pandas, Matplotlib
• Scikit-learn (just starting)

Setup

pip install numpy pandas matplotlib scikit-learn jupyter
jupyter notebook

Goals

• Build strong fundamentals in supervised and unsupervised learning
• Apply ML to mechanical engineering problems (predictive maintenance, fluid simulation, FEA optimization)
• Eventually work on physics-informed neural networks (PINNs)

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Hidekel Irizarry | Mechanical Engineering @ UCF
Book: Hands-On Machine Learning, 3rd Ed. — Aurélien Géron