microsoft / ml-wrappers
A unified wrapper for various ML frameworks - to have one uniform scikit-learn format for predict and predict_proba functions.
ā48Updated 3 months ago
Alternatives and similar repositories for ml-wrappers:
Users that are interested in ml-wrappers are comparing it to the libraries listed below
- Unified slicing for all Python data structures.ā35Updated 2 months ago
- š Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projectsā81Updated 3 years ago
- Managing Data and Model Drift with Azure Machine Learningā43Updated 2 years ago
- ForML - A development framework and MLOps platform for the lifecycle management of data science projectsā106Updated last year
- DataFrame support for scikit-learn.ā63Updated last year
- Turning AML compute into Ray clusterā77Updated 2 years ago
- Project for open sourcing research efforts on Backward Compatibility in Machine Learningā73Updated last year
- Providing tools and templates to facilitate modern MLOps practicesā83Updated 8 months ago
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.ā65Updated 2 months ago
- Samples for NimbusML, a Python machine learning package providing simple interoperability between ML.NET and scikit-learn components.ā37Updated 5 years ago
- Azure plugins for Feast (FEAture STore)ā82Updated last year
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world dā¦ā428Updated 2 months ago
- Capturing model drift and handling its response - Example webinarā108Updated 5 years ago
- Template for getting started with automated ML Ops on Azure Machine Learningā128Updated 2 years ago
- Projects developed by Domino's R&D teamā76Updated 3 years ago
- An abstraction layer for parameter tuningā35Updated 7 months ago
- Python library for implementing Responsible AI mitigations.ā65Updated last year
- Example of using HyperDrive to tune a regular ML learner.ā60Updated 5 years ago
- Shows how to spin up a DASK cluster on AML Computeā29Updated 3 years ago
- Instant search for and access to many datasets in Pyspark.ā34Updated 2 years ago
- Cyclic Boosting Machines - an explainable supervised machine learning algorithmā60Updated 7 months ago
- Code samples for the Effective Data Science Infrastructure bookā115Updated last year
- HiPlot fetcher for experiments logged with MLflowā14Updated 2 years ago
- GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations