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.
machine-learning/
└── Ch2/
└── test.ipynb # Chapter 2 — End-to-End ML Project (California Housing)
| 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 |
- Python 3
- Jupyter Notebooks
- NumPy, Pandas, Matplotlib
- Scikit-learn (just starting)
pip install numpy pandas matplotlib scikit-learn jupyter
jupyter notebook- 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)
Hidekel Irizarry | Mechanical Engineering @ UCF
Book: Hands-On Machine Learning, 3rd Ed. — Aurélien Géron