Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.
Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes
Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure.
Prophecis is a one-stop cloud native machine learning platform.
Run Slurm in Kubernetes
A holistic way of understanding how Llama and its components run in practice, with code and detailed documentation.
LLaMA-2 in native Go
Transform your pythonic research to an artifact that engineers can deploy easily.
Experiment tracking server focused on speed and scalability
Extensible generative AI platform on Kubernetes with OpenAI-compatible APIs.
A project to demonstrate an approach to designing cross-language and distributed pipeline in deep learning/machine learning domain, using WebRTC and Redis Streams.
Go ML/AI Training Materials for GopherCon 2019
Eternal is an experimental platform for machine learning models and workflows.
SRC (Shared Recruiting Co.) is an open-source, candidate-centric recruiting platform
Sister project to OpenLLMetry, but in Go. Open-source observability for your LLM application, based on OpenTelemetry