Jupyter and Pluto notebooks for Operations Research Problems

A teaching collection of handwritten PDF and Julia/Pluto notebooks, mainly numerical mathematics, optimization, partial differenatial equations and related topics.

All notebooks used to generate results and figures in the paper linked below.

Slides/notes and Jupyter notebook demos for an introductory course of numerical analysis/scientific computing

Repository for the companion Colab notebook of the Domain-Specific Small Language Models book.

From the popular book "Mathematics for Machine Learning". My solutions to the exercises from Part I. Also, notebooks with concrete examples of concepts from Part II.

📶 Logistic regression classifier for bit decoding in binary vectors using stochastic gradient descent (SGD). Features performance evaluation, probabilistic modeling, confusion matrix analysis, and classification error interpretation. Developed in Python with Jupyter Notebook.

A comprehensive collection of Jupyter notebooks demonstrating advanced mathematical concepts using SageMath. Covers calculus, linear algebra, number theory, cryptography, optimization, and computational mathematics with interactive visualizations.

Supply Chain Analytics - Notebooks for classroom.

🔬 SciPyMasterPro — A hands-on, modular project to master SciPy for statistics, optimization, linear algebra, curve fitting, and simulations. Includes 10+ Jupyter notebooks, an interactive Streamlit app, synthetic datasets, reusable utility functions, Dockerized setup, and cheatsheets for fast recall, portfolio building, and interview prep.

This project solves the Maximum Clique Problem using continuous optimization algorithms like Projected Gradient Descent and Frank-Wolfe, implemented in a Jupyter Notebook.

A curated workshop of Jupyter notebooks and deep-dive PDFs that break down how large language models work , from kv-cache internals and fine-tuning to optimization strategies and skill paths. Ideal for engineers who want to go beyond APIs and really understand the guts of LLMs.

Comprehensive codebase for my thesis on the Hybrid Flexible Flow-shop (HFFS) problem, featuring implementations and experiments for two metaheuristics (Genetic Algorithm, ALNS), instance generation scripts, and complete analysis notebooks for result replication. See the thesis PDF for details.

A from-scratch implementation of reverse automatic differentiation and gradient descent in C++, featuring Python bindings for Jupyter notebook integration.

Jupyter Notebook tool enabling users to research, optimize, and manage their Fantasy Premier League teams.

Use a quantum computer to decode cellphone signals

Materials for the optimization course [Matlab, Python and Julia]

A small agglomerates of one jupyter notebook projects just to try stuff out.

Jupyter notebooks about Programming, Statistics and Math

Optimization notebooks