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RF-DETR is a Python library for training and deploying object detection, instance segmentation, and keypoint detection models built on a vision transformer architecture. It provides a unified command-line interface and Python API for the full workflow, from fine-tuning pretrained checkpoints on custom datasets to running inference on images, video files, and live camera streams. The project supports training on datasets in COCO or YOLO format, with automatic format detection and configurable augmentation pipelines. Models can be exported to ONNX, TFLite, or TensorRT for deployment across edge
PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It functions as a low-code environment that leverages a scikit-learn native engine to execute preprocessing, training, and evaluation for tabular data. The platform distinguishes itself as an LLM-powered ML copilot, using large language model agents to analyze datasets, design experiment configurations, and explain model results. It also serves as a Kubernetes ML orchestrator and model registry, enabling the versioning of trained pipelines and their promotion to production API endp
Examples of Machine Learning code using Comet.ml
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
The main features of henripal/labnotebook are: Experiment Tracking.
Open-source alternatives to henripal/labnotebook include: roboflow/rf-detr — RF-DETR is a Python library for training and deploying object detection, instance segmentation, and keypoint detection… pycaret/pycaret — PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It… comet-ml/comet-examples — Examples of Machine Learning code using Comet.ml. guildai/guildai — Experiment tracking, ML developer tools. idsia/sacred — Sacred is an experiment management tool and reproducibility framework designed to organize multiple runs of a process… kedro-org/kedro-viz — Visualise your Kedro data and machine-learning pipelines and track your experiments.
