Course materials for General Assembly's Data Science course in Washington, DC (12/15/14 - 3/16/15). Use it to build a structured path from fundamentals to hands-on practice.

A curated list of awesome Bioinformatics software, resources, and libraries. Mostly command line based, and free or open-source. Please feel free to contribute!. Use it as a repeatable review, validation or hardening pass.

A curated reference on scientific & biomedical data centered on A 3D multi-modal medical image segmentation library in PyTorch. Use it to ground design choices in named patterns, trade-offs and examples.

This is a curated list of medical data for machine learning. This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here. Use it to ground design choices in named patterns, trade-offs and examples.

Segment Anything Model (SAM) uses vision transformer-based image encoder to extract image features and compute an image embedding, and prompt encoder to embed prompts and incorporate user interactions. Then extranted information from two encoders are combined to alightweight mask. Use it to navigate the topic and choose relevant methods, papers or tools.

The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifecycle. AI Fairness 360 package is available in both Python and. Use it to navigate the topic and choose relevant methods, papers or tools.

Kaolin packages reusable building blocks from NVIDIA 3D research into a cohesive PyTorch API — continuously improving representation-agnostic physics simulation, fast conversions between representations, quaternion math, batched mesh and splat containers, I/O, visualization and m. Use it to build a structured path from fundamentals to hands-on practice.

An interactive deep learning book with code, math, and discussions, based on the NumPy interface by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola. With 900 pages, this seems to be one of the most comprehensive one-stop resources that goes from Linear Neural Networ. Use it to build a structured path from fundamentals to hands-on practice.

First open-source project — fully-local on a single RTX 3090 (Qwen3.6-27B) — to report 95% SimpleQA (n=500) and 77% xbench-DeepSearch (n=100) on local hardware. See the r/LocalLLaMA announcement and the benchmark dataset. Use it as a repeatable review, validation or hardening pass.

Overview of medical image segmentation challenges in MICCAI 2023. Use it to navigate the topic and choose relevant methods, papers or tools.

This repo has all the resources you need to become an amazing data engineer!. Use it to build a structured path from fundamentals to hands-on practice.