Machine Learning for Physics Enthusiasts
The entire field of machine learning (including deep learning) can be explained by just one equation:
\[P=\frac{e^{-F}}{Z}\]
And, we always need to ask a single question: "How do we find \(F\) using data?"
In the courses below, we will answer this question for various machine learning models.
Here’s your roadmap:
🎬 Start from Episode 1 and move through the episodes step by step 👣.- ✨ Read the Note to understand concepts.
- 🚀 Take the Course on Google Colab.
- 🎯 Run the Intermediate Project.
- 🌟 Add complexities of professional setting to intermediate projects and prepare for deployment.
- 🎓 Want to learn it all & even more systematically? Apply to our BootCamp!
Episodes
| Notes | Course | Intermediate Project | Advanced Project |
|---|---|---|---|
| Linear Regression | Course | Project | Apply to BootCamp! |
| Loss Function | coming soon | coming soon | coming soon |
| Residual Sum of Squares | coming soon | coming soon | coming soon |
| Gradient Descent | coming soon | coming soon | coming soon |
| Bias Variance TradeOff | coming soon | coming soon | coming soon |
| Regularization | coming soon | coming soon | coming soon |
| Feature Engineering and Selection | coming soon | coming soon | coming soon |
| Probabilistic basis of ML | coming soon | coming soon | coming soon |
| Polynomial Regression | coming soon | coming soon | coming soon |
| Logistic Regression | coming soon | coming soon | coming soon |
| Multinomial Logistic Regression | coming soon | coming soon | coming soon |
| Support Vector Machine (SVM) | coming soon | coming soon | coming soon |
| Kernels | coming soon | coming soon | coming soon |
| K-Nearest Neighbors (KNN) | coming soon | coming soon | coming soon |
Citation
How to cite this work:
If you use or reference material from this collection, please cite as:
Borzou, Ardavan. 2025. Machine Learning for Physics Enthusiasts. CompuFlair. https://compu-flair.com/ml-for-physicists
BibTeX:
@misc{borzou2025mlphysics,
author = {Borzou, Ardavan},
title = {Machine Learning for Physics Enthusiasts},
year = { 2025 },
url = {https://compu-flair.com/ml-for-physicists},
note = {Accessed: 2025-11-23"}
}