No project description provided
Project description
Machine learning (ML) pipelines are used by data scientists to build, optimize, and manage their machine learning workflows. A typical pipeline involves a sequence of steps that cover the following areas:
Data preparation, such as normalizations and transformations
Model training, such as hyper parameter tuning and validation
Model deployment and evaluation
The Azure Machine Learning SDK for Python can be used to create ML pipelines as well as to submit and track individual pipeline runs.
Module and ModuleVersion classes are added to manage reusable compute units in pipelines.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file azureml_pipeline-1.0.69-py3-none-any.whl.
File metadata
- Download URL: azureml_pipeline-1.0.69-py3-none-any.whl
- Upload date:
- Size: 3.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.5.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
49b8c8a3d27dfe4a57656587e153326021fa2ca57c38f40c389464e3be090d79
|
|
| MD5 |
4d4edd4225c98fa7970fdf8610aa2676
|
|
| BLAKE2b-256 |
519f9a5c61cc1284661fa3811c37504ec8704dc6ed758e8d1ad2ad301bd5d085
|
