Study notes and code exploring NumPy, pandas, and data-wrangling fundamentals in Python.
Hands-on study notes across practical ML and data topics.
Study notes and code exploring TensorFlow and Keras fundamentals.
Computer vision study notes using OpenCV 3 and Python.
Study notes on applying deep learning techniques to computer vision tasks.
Study notes on reinforcement-learning fundamentals and implementations in TensorFlow.
Study notes and Python implementations of core data structures and algorithms.
Study notes on scraping, parsing, and automating web-data extraction in Python.
Study notes on deep-learning foundations and Python implementations.
A public release of reusable Python code — utilities, analysis helpers, and one-off scripts.
Study notes and code on probabilistic programming and Bayesian inference (PyMC-based).
Trained iQNet v1 neural networks using HST and HST+SDSS training spectra.
Hands-on PyTorch tutorial notebooks, runnable in Google Colab.
Study notes and examples for building desktop GUIs with PyQt5.
Course materials used for the CDSA 2022 Computational Courses.
Brief study notes from d2l.ai's open "Dive into Deep Learning" textbook.
A running collection of reusable PyTorch recipes — training loops, dataloaders, and common patterns.
Notes and code following Sebastian Raschka's "Build a Large Language Model (from Scratch)" book.
Notes and experiments with graph-based retrieval-augmented generation (GraphRAG).
An agentic data scientist for ML and DL workflows.
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