A couple of mysql defining the key relationships for Plasma cut charts.

Automatic extraction of relevant features from time series:

Bresser 5-in-1/6-in-1/7-in-1 868 MHz Weather Sensor Radio Receiver for Arduino based on CC1101, SX1276/RFM95W or SX1262

Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024

Tutorial Materials for "The Fundamentals of Modern Deep Learning with PyTorch" workshop at PyCon 2024

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

Software for "Guide to gyro and accelerometer with Arduino including Kalman filtering"

A Repo For Document AI

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

Excel-DNA extension for Excel written in .NET demonstrating many features provided by Excel-DNA.

Mesa Configuration Tool II

Causal inference tutorials written as part of the Data Analysis Tools for Atmospheric Scientists (DATAS) Gateway.

🍦 Never use print() to debug again.

VBA-Web: Connect VBA, Excel, Access, and Office for Windows and Mac to web services and the web

An easy and fast way to create a Python GUI 🐍

To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

Graph Neural Network Library for PyTorch

Material for the hands-on tutorial on Graph Deep Learning held at the Alan Turing Institute

Test-Driven Data Analysis Functions

Data processing with ML and LLM

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

A Library for Uncertainty Quantification.

Go ahead and axolotl questions

Awesome-LLM: a curated list of Large Language Model

A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.