This is the Linux app named MLflow whose latest release can be downloaded as MLflow2.7.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
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MLflow
DESCRIPTION
MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud).
Features
- MLflow Tracking: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.
- MLflow Projects: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others.
- MLflow Models: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker.
- MLflow Model Registry: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.
Programming Language
Python, JavaScript
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/mlflow.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
