mlflow

The open source developer platform to build AI/LLM applications and models with confidence. Enhance your AI applications with end-to-end tracking, observability, and evaluations, all in one integrated platform.

https://github.com/mlflow/mlflow

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
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Academic publication links
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Committers with academic emails
26 of 838 committers (3.1%) from academic institutions
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (13.1%) to scientific vocabulary

Keywords

agentops agents ai ai-governance apache-spark evaluation langchain llm-evaluation llmops machine-learning ml mlflow mlops model-management observability open-source openai prompt-engineering

Keywords from Contributors

application rag multi-agents vector-database llamaindex fine-tuning closember data-mining cryptocurrencies jax

Scientific Fields

Engineering Computer Science - 60% confidence

Earth and Environmental Sciences Physical Sciences - 40% confidence

Last synced: 4 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: mlflow
License: apache-2.0
Language: Python
Default Branch: master
Homepage: https://mlflow.org
Size: 855 MB

Statistics

Stars: 21,833
Watchers: 315
Forks: 4,784
Open Issues: 1,974
Releases: 0

Topics

agentops agents ai ai-governance apache-spark evaluation langchain llm-evaluation llmops machine-learning ml mlflow mlops model-management observability open-source openai prompt-engineering

Created over 7 years ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation Security

README.md

Open-Source Platform for Productionizing AI

MLflow is an open-source developer platform to build AI/LLM applications and models with confidence. Enhance your AI applications with end-to-end experiment tracking, observability, and evaluations, all in one integrated platform.

[![Python SDK](https://img.shields.io/pypi/v/mlflow)](https://pypi.org/project/mlflow/) [![PyPI Downloads](https://img.shields.io/pypi/dm/mlflow)](https://pepy.tech/projects/mlflow) [![License](https://img.shields.io/github/license/mlflow/mlflow)](https://github.com/mlflow/mlflow/blob/main/LICENSE)

[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/mlflow/mlflow)

Website Docs Feature Request News YouTube Events

Installation

To install the MLflow Python package, run the following command:

pip install mlflow

Core Components

MLflow is the only platform that provides a unified solution for all your AI/ML needs, including LLMs, Agents, Deep Learning, and traditional machine learning.

For LLM / GenAI Developers

Tracing / Observability Trace the internal states of your LLM/agentic applications for debugging quality issues and monitoring performance with ease. Getting Started	LLM Evaluation A suite of automated model evaluation tools, seamlessly integrated with experiment tracking to compare across multiple versions. Getting Started
Prompt Management Version, track, and reuse prompts across your organization, helping maintain consistency and improve collaboration in prompt development. Getting Started	App Version Tracking MLflow keeps track of many moving parts in your AI applications, such as models, prompts, tools, and code, with end-to-end lineage. Getting Started

For Data Scientists

Experiment Tracking Track your models, parameters, metrics, and evaluation results in ML experiments and compare them using an interactive UI. Getting Started
Model Registry A centralized model store designed to collaboratively manage the full lifecycle and deployment of machine learning models. Getting Started	Deployment Tools for seamless model deployment to batch and real-time scoring on platforms like Docker, Kubernetes, Azure ML, and AWS SageMaker. Getting Started

Hosting MLflow Anywhere

You can run MLflow in many different environments, including local machines, on-premise servers, and cloud infrastructure.

Trusted by thousands of organizations, MLflow is now offered as a managed service by most major cloud providers:

For hosting MLflow on your own infrastructure, please refer to this guidance.

Supported Programming Languages

Integrations

MLflow is natively integrated with many popular machine learning frameworks and GenAI libraries.

Integrations

Usage Examples

Experiment Tracking (Doc)

The following examples trains a simple regression model with scikit-learn, while enabling MLflow's autologging feature for experiment tracking.

```python import mlflow

from sklearn.modelselection import traintestsplit from sklearn.datasets import loaddiabetes from sklearn.ensemble import RandomForestRegressor

Enable MLflow's automatic experiment tracking for scikit-learn

mlflow.sklearn.autolog()

Load the training dataset

db = loaddiabetes() Xtrain, Xtest, ytrain, ytest = traintest_split(db.data, db.target)

rf = RandomForestRegressor(nestimators=100, maxdepth=6, max_features=3)

MLflow triggers logging automatically upon model fitting

rf.fit(Xtrain, ytrain) ```

Once the above code finishes, run the following command in a separate terminal and access the MLflow UI via the printed URL. An MLflow Run should be automatically created, which tracks the training dataset, hyper parameters, performance metrics, the trained model, dependencies, and even more.

mlflow ui

Evaluating Models (Doc)

The following example runs automatic evaluation for question-answering tasks with several built-in metrics.

```python import mlflow import pandas as pd

Evaluation set contains (1) input question (2) model outputs (3) ground truth

df = pd.DataFrame( { "inputs": ["What is MLflow?", "What is Spark?"], "outputs": [ "MLflow is an innovative fully self-driving airship powered by AI.", "Sparks is an American pop and rock duo formed in Los Angeles.", ], "groundtruth": [ "MLflow is an open-source platform for productionizing AI.", "Apache Spark is an open-source, distributed computing system.", ], } ) evaldataset = mlflow.data.frompandas( df, predictions="outputs", targets="groundtruth" )

Start an MLflow Run to record the evaluation results to

with mlflow.startrun(runname="evaluateqa"): # Run automatic evaluation with a set of built-in metrics for question-answering models results = mlflow.evaluate( data=evaldataset, model_type="question-answering", )

print(results.tables["evalresultstable"]) ```

Observability (Doc)

MLflow Tracing provides LLM observability for various GenAI libraries such as OpenAI, LangChain, LlamaIndex, DSPy, AutoGen, and more. To enable auto-tracing, call mlflow.xyz.autolog() before running your models. Refer to the documentation for customization and manual instrumentation.

```python import mlflow from openai import OpenAI

Enable tracing for OpenAI

mlflow.openai.autolog()

Query OpenAI LLM normally

response = OpenAI().chat.completions.create( model="gpt-4o-mini", messages=[{"role": "user", "content": "Hi!"}], temperature=0.1, ) ```

Then navigate to the "Traces" tab in the MLflow UI to find the trace records OpenAI query.

Support

For help or questions about MLflow usage (e.g. "how do I do X?") visit the documentation.
In the documentation, you can ask the question to our AI-powered chat bot. Click on the "Ask AI" button at the right bottom.
Join the virtual events like office hours and meetups.
To report a bug, file a documentation issue, or submit a feature request, please open a GitHub issue.
For release announcements and other discussions, please subscribe to our mailing list (mlflow-users@googlegroups.com) or join us on Slack.

Contributing

We happily welcome contributions to MLflow!

Submit bug reports and feature requests
Contribute for good-first-issues and help-wanted
Writing about MLflow and sharing your experience

Please see our contribution guide to learn more about contributing to MLflow.

Star History

Citation

If you use MLflow in your research, please cite it using the "Cite this repository" button at the top of the GitHub repository page, which will provide you with citation formats including APA and BibTeX.

Core Members

MLflow is currently maintained by the following core members with significant contributions from hundreds of exceptionally talented community members.

Owner

Name: MLflow
Login: mlflow
Kind: organization

Website: https://www.mlflow.org
Repositories: 12
Profile: https://github.com/mlflow

Open source platform for the machine learning lifecycle

Committers

Last synced: 8 months ago

All Time

Total Commits: 7,599
Total Committers: 838
Avg Commits per committer: 9.068
Development Distribution Score (DDS): 0.722

Past Year

Commits: 1,811
Committers: 160
Avg Commits per committer: 11.319
Development Distribution Score (DDS): 0.728

Top Committers

Name	Email	Commits
Harutaka Kawamura	h**0@g**m	2,111
dbczumar	3****r	423
Yuki Watanabe	3****2	381
Serena Ruan	8****n	318
Ben Wilson	3****2	292
Siddharth Murching	s**g@d**m	272
mlflow-automation	6****n	261
WeichenXu	w**u@d**m	254
Daniel Lok	d**k@d**m	195
Sunish Sheth	s**9@g**m	134
Aaron Davidson	a**n@d**m	128
Prithvi Kannan	4****n	106
TomuHirata	t**a@g**m	96
Chen Qian	c**y@g**m	90
tomasatdatabricks	3****s	90
Mani Parkhe	m**i@d**m	89
Jerry Liang	6****b	68
Ann Zhang	a**g@d**m	62
apurva-koti	5****i	61
Sue Ann Hong	s**n@d**m	48
Liang Zhang	l**g@d**m	47
Andrew Chen	a**n@b**u	44
juntai-zheng	3****g	44
Stephanie Bodoff	s**f@d**m	44
Matei Zaharia	m****z	37
Gabriel Fu	h**l@g**m	37
Ankit Mathur	5****b	32
Michael Berk	m**9@g**m	30
Bryan Qiu	5****u	30
dmatrix	d**x@c**t	29
and 808 more...

Committer Domains (Top 20 + Academic)

databricks.com: 33 qq.com: 4 microsoft.com: 4 criteo.com: 3 me.com: 3 mail.utoronto.ca: 2 poli.ufrj.br: 2 wustl.edu: 2 cornell.edu: 2 expedia.com: 2 jhallard.com: 1 qucit.com: 1 fnal.gov: 1 grid.ai: 1 neijt.nl: 1 163.com: 1 ischool.berkeley.edu: 1 seldon.io: 1 cacharle.xyz: 1 umbocv.com: 1 berkeley.edu: 1 andrew.cmu.edu: 1 student.manchester.ac.uk: 1 mail.uc.edu: 1 klis.tsukuba.ac.jp: 1 kth.se: 1 uw.edu: 1 dons.usfca.edu: 1 utexas.edu: 1 brown.edu: 1 aqueducthq.com: 1 uci.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 1,881
Total pull requests: 9,620
Average time to close issues: 7 months
Average time to close pull requests: 8 days
Total issue authors: 1,222
Total pull request authors: 524
Average comments per issue: 3.43
Average comments per pull request: 1.66
Merged pull requests: 6,781
Bot issues: 0
Bot pull requests: 166

Past Year

Issues: 705
Pull requests: 5,164
Average time to close issues: 6 days
Average time to close pull requests: 3 days
Issue authors: 426
Pull request authors: 237
Average comments per issue: 1.22
Average comments per pull request: 1.53
Merged pull requests: 3,527
Bot issues: 0
Bot pull requests: 152

View more stats

Top Authors

Issue Authors

harupy (198)
BenWilson2 (22)
chenmoneygithub (22)
B-Step62 (19)
kimminw00 (18)
danilopeixoto (13)
amesar (12)
ai-learner-00 (11)
mazer-ai (11)
dannikay (10)
Gumichocopengin8 (10)
dbczumar (8)
Flametaa (8)
harshilprajapati96 (7)
smurching (7)

Pull Request Authors

harupy (2,459)
B-Step62 (1,172)
serena-ruan (765)
daniellok-db (556)
WeichenXu123 (385)
mlflow-automation (365)
BenWilson2 (327)
TomeHirata (268)
prithvikannan (182)
dbczumar (170)
mlflow-app[bot] (152)
Copilot (142)
chenmoneygithub (130)
sunishsheth2009 (129)
annzhang-db (115)

Top Labels

Issue Labels

bug (799) enhancement (528) has-closing-pr (400) area/tracking (278) area/uiux (214) area/models (164) good first issue (151) area/artifacts (143) area/docs (140) area/model-registry (100) help wanted (69) area/server-infra (64) area/docker (54) integrations/databricks (49) area/deployments (49) area/build (44) area/sqlalchemy (44) area/scoring (43) area/projects (42) priority/important-longterm (41) area/examples (36) integrations/azure (33) priority/backlog (32) rn/none (27) priority/important-soon (22) stale (21) priority/awaiting-more-evidence (21) Acknowledged (20) area/windows (18) integrations/sagemaker (18)

Pull Request Labels

rn/none (5,923) area/tracking (1,301) rn/feature (729) area/docs (611) rn/bug-fix (545) area/models (508) area/build (340) team-review (289) rn/documentation (288) enable-dev-tests (210) area/model-registry (154) area/uiux (131) area/artifacts (121) patch-2.13.1 (113) patch-2.12.2 (107) v2.21.0 (100) integrations/databricks (82) v3.1.0 (78) area/deployments (76) rn/breaking-change (75) v2.20.0 (74) patch-2.16.1 (71) v2.22.1 (70) area/examples (68) area/tracing (66) area/scoring (65) area/server-infra (63) v3.1.2 (60) py39 (58) v3.0.0 (57)

Packages

Total packages: 31
Total downloads:
- pypi 46,230,924 last-month
- npm 518 last-month
- cran 28,785 last-month
Total docker downloads: 31,596,326

Total dependent packages: 426
(may contain duplicates)
Total dependent repositories: 5,273
(may contain duplicates)
Total versions: 1,257
Total maintainers: 25
Total advisories: 53

pypi.org: mlflow

MLflow is an open source platform for the complete machine learning lifecycle

Documentation: https://mlflow.readthedocs.io/
License: Copyright 2018 Databricks, Inc. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Latest release: 3.3.2
published 4 months ago

Versions: 153
Dependent Packages: 360
Dependent Repositories: 5,089
Downloads: 21,738,565 Last month
Docker Downloads: 24,823,885

Rankings

Downloads: 0.1%

Dependent packages count: 0.1%

Dependent repos count: 0.1%

Forks count: 0.2%

Average: 0.2%

Stargazers count: 0.3%

Docker downloads count: 0.7%

Maintainers (13)

dbczumar andrewmchen databricks mateiz paul.ogilvie smurching sueanndb harupy benwilson weichenxu123 serenaruan B-Step62 daniellok-db

Advisories (53)

Last synced: 4 months ago

pypi.org: mlflow-skinny

MLflow is an open source platform for the complete machine learning lifecycle

Documentation: https://mlflow-skinny.readthedocs.io/
License: Copyright 2018 Databricks, Inc. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. 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For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Latest release: 3.3.2
published 4 months ago

Versions: 114
Dependent Packages: 49
Dependent Repositories: 70
Downloads: 21,131,789 Last month
Docker Downloads: 6,743,241

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Downloads: 0.2%

Dependent packages count: 0.4%

Average: 0.6%

Docker downloads count: 1.1%

Dependent repos count: 1.8%

Maintainers (8)

dbczumar smurching harupy benwilson weichenxu123 serenaruan B-Step62 daniellok-db

Last synced: 4 months ago

conda-forge.org: mlflow

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 2.0.1
published about 3 years ago

Versions: 43
Dependent Packages: 9
Dependent Repositories: 40

Rankings

Forks count: 1.9%

Stargazers count: 2.2%

Average: 4.0%

Dependent repos count: 5.6%

Dependent packages count: 6.4%

Last synced: 4 months ago

repo1.maven.org: org.mlflow:mlflow-client

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-client/
License: The Apache License, Version 2.0
Latest release: 3.3.2
published 4 months ago

Versions: 120
Dependent Packages: 8
Dependent Repositories: 24
Docker Downloads: 661

Rankings

Stargazers count: 1.6%

Forks count: 2.4%

Average: 4.1%

Docker downloads count: 4.5%

Dependent repos count: 4.8%

Dependent packages count: 7.3%

Last synced: 4 months ago

proxy.golang.org: github.com/mlflow/mlflow

Documentation: https://pkg.go.dev/github.com/mlflow/mlflow#section-documentation
License: apache-2.0
Latest release: v2.18.0+incompatible
published about 1 year ago

Versions: 104
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 0.1%

Stargazers count: 0.5%

Average: 4.2%

Dependent packages count: 7.0%

Dependent repos count: 9.3%

Last synced: about 1 year ago

cran.r-project.org: mlflow

Interface to 'MLflow'

Homepage: https://github.com/mlflow/mlflow
Documentation: http://cran.r-project.org/web/packages/mlflow/mlflow.pdf
License: Apache License 2.0
Latest release: 3.3.2
published 4 months ago

Versions: 66
Dependent Packages: 0
Dependent Repositories: 2
Downloads: 28,785 Last month
Docker Downloads: 28,005

Rankings

Stargazers count: 0.0%

Forks count: 0.0%

Downloads: 3.0%

Docker downloads count: 6.4%

Average: 9.5%

Dependent repos count: 19.6%

Dependent packages count: 28.0%

Maintainers (1)

benjamin.wilson@databricks.com

Last synced: 4 months ago

pypi.org: mlflow-devlibx

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 1.22.8
published almost 4 years ago

Versions: 9
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 65 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.4%

Average: 11.7%

Dependent repos count: 22.2%

Downloads: 28.5%

Maintainers (1)

devlibx

Last synced: 4 months ago

pypi.org: mlflow-tmp

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 2.2.26
published over 2 years ago

Versions: 25
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 87 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.3%

Average: 12.1%

Dependent repos count: 40.9%

Maintainers (1)

ckloan

Last synced: 4 months ago

npmjs.org: mlflow-tracing

TypeScript implementation of MLflow Tracing SDK for LLM observability

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 0.1.0
published 4 months ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 310 Last month

Rankings

Forks count: 0.4%

Stargazers count: 0.5%

Average: 15.0%

Dependent repos count: 24.1%

Dependent packages count: 34.8%

Maintainers (1)

yuki_watanabe

Last synced: 4 months ago

pypi.org: mlflow-tracing

MLflow Tracing SDK is an open-source, lightweight Python package that only includes the minimum set of dependencies and functionality to instrument your code/models/agents with MLflow Tracing.

Documentation: https://mlflow-tracing.readthedocs.io/
License: Copyright 2018 Databricks, Inc. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. 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You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Latest release: 3.3.2
published 4 months ago

Versions: 13
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 3,359,909 Last month

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Forks count: 0.3%

Stargazers count: 0.4%

Dependent packages count: 9.2%

Average: 15.5%

Dependent repos count: 51.9%

Maintainers (5)

harupy benwilson serenaruan B-Step62 TomeHirata

Last synced: 4 months ago

repo1.maven.org: org.mlflow:mlflow-scoring

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-scoring/
License: The Apache License, Version 2.0
Latest release: 2.22.1
published 7 months ago

Versions: 109
Dependent Packages: 0
Dependent Repositories: 1
Docker Downloads: 493

Rankings

Stargazers count: 1.6%

Forks count: 2.4%

Docker downloads count: 4.1%

Average: 15.7%

Dependent repos count: 20.6%

Dependent packages count: 49.9%

Last synced: 4 months ago

pypi.org: mlflow-stonewise

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 1.30.1
published almost 3 years ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 27 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 6.6%

Average: 16.8%

Dependent repos count: 30.6%

Downloads: 46.4%

Maintainers (1)

liuweibin

Last synced: 4 months ago

pypi.org: lmcmlflow

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 1.17.1
published over 4 years ago

Versions: 3
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 10 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.4%

Average: 17.2%

Dependent repos count: 22.2%

Downloads: 56.0%

Maintainers (1)

jhettler

Last synced: 4 months ago

pypi.org: mlflow-by-johnsnowlabs

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 2.40.0
published about 2 years ago

Versions: 35
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 115 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.5%

Downloads: 11.3%

Average: 17.8%

Dependent repos count: 69.8%

Maintainers (1)

ckloan

Last synced: 4 months ago

pypi.org: mlflow-ste

MLflow: An ML Workflow Tool

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 1.10.1.dev0
published over 5 years ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 27 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.4%

Average: 17.9%

Dependent repos count: 22.2%

Downloads: 59.9%

Maintainers (1)

xstex

Last synced: 4 months ago

repo1.maven.org: org.mlflow:mlflow-parent

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-parent/
License: The Apache License, Version 2.0
Latest release: 3.3.2
published 4 months ago

Versions: 120
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Stargazers count: 1.6%

Forks count: 2.4%

Average: 18.6%

Dependent repos count: 20.6%

Dependent packages count: 49.9%

Last synced: 4 months ago

repo1.maven.org: org.mlflow:mlflow-spark

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-spark/
License: The Apache License, Version 2.0
Latest release: 2.8.1
published about 2 years ago

Versions: 57
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Stargazers count: 1.6%

Forks count: 2.4%

Average: 18.6%

Dependent repos count: 20.6%

Dependent packages count: 49.9%

Last synced: 4 months ago

pypi.org: mlflow-by-ckl

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 2.81.0
published over 1 year ago

Versions: 44
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 234 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.3%

Average: 19.1%

Dependent repos count: 68.7%

Maintainers (2)

ckloan mehmetbutgul

Last synced: 4 months ago

pypi.org: mlflow-by-johnsnowlabs-v2

MLflow: A Platform for ML Development and Productionization

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 2.44.0
published over 2 years ago

Versions: 9
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 48 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.4%

Average: 19.2%

Dependent repos count: 69.2%

Maintainers (1)

ckloan

Last synced: 4 months ago

anaconda.org: mlflow

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).

Homepage: https://mlflow.org
License: Apache-2.0
Latest release: 2.18.0
published about 1 year ago

Versions: 7
Dependent Packages: 0
Dependent Repositories: 40

Rankings

Forks count: 5.5%

Stargazers count: 6.1%

Average: 19.7%

Dependent repos count: 26.0%

Dependent packages count: 41.0%

Last synced: 4 months ago

pypi.org: qubole-ml

MLflow: An ML Workflow Tool

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 1.9.1
published over 5 years ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 7 Last month

Rankings

Forks count: 0.1%

Stargazers count: 0.1%

Dependent packages count: 7.4%

Average: 20.2%

Dependent repos count: 22.2%

Downloads: 71.1%

Maintainers (1)

qubole

Last synced: 4 months ago

pypi.org: mlflow-saagie

MLflow: A Platform for ML Development and Productionization - forked for Saagie

Homepage: https://mlflow.org/
Documentation: https://mlflow.org/docs/latest/index.html
License: Apache License 2.0
Latest release: 2.9.2
published almost 2 years ago

Versions: 8
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 28 Last month
Docker Downloads: 41

Rankings

Docker downloads count: 3.8%

Dependent packages count: 10.1%

Average: 21.2%

Dependent repos count: 21.6%

Forks count: 22.6%

Downloads: 30.3%

Stargazers count: 38.8%

Maintainers (1)

service

Last synced: 4 months ago

conda-forge.org: mlflow-skinny

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 2.0.1
published about 3 years ago

Versions: 23
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 1.8%

Stargazers count: 2.2%

Average: 22.3%

Dependent repos count: 34.0%

Dependent packages count: 51.2%

Last synced: 4 months ago

conda-forge.org: r-mlflow

Homepage: https://github.com/mlflow/mlflow
License: Apache-2.0
Latest release: 1.30.0
published about 3 years ago

Versions: 33
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 1.8%

Stargazers count: 2.2%

Average: 22.3%

Dependent repos count: 34.0%

Dependent packages count: 51.2%

Last synced: 4 months ago

conda-forge.org: mlflow-pipelines

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 1.30.0
published about 3 years ago

Versions: 3
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 1.8%

Stargazers count: 2.2%

Average: 22.3%

Dependent repos count: 34.0%

Dependent packages count: 51.2%

Last synced: 4 months ago

conda-forge.org: mlflow-ui-dbg

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 2.0.1
published about 3 years ago

Versions: 41
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 1.8%

Stargazers count: 2.2%

Average: 22.3%

Dependent repos count: 34.0%

Dependent packages count: 51.2%

Last synced: 4 months ago

anaconda.org: mlflow-skinny

MLflow Skinny is a lightweight MLflow package without SQL storage, server, UI, or data science dependencies.

Homepage: https://mlflow.org
License: Apache-2.0
Latest release: 2.18.0
published about 1 year ago

Versions: 7
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 5.8%

Stargazers count: 6.5%

Average: 29.0%

Dependent packages count: 43.4%

Dependent repos count: 60.1%

Last synced: 4 months ago

npmjs.org: mlflow-openai

OpenAI integration package for MLflow Tracing

Homepage: https://mlflow.org/
License: Apache-2.0
Latest release: 0.1.0
published 4 months ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 208 Last month

Rankings

Dependent repos count: 24.1%

Average: 29.5%

Dependent packages count: 34.8%

Maintainers (1)

yuki_watanabe

Last synced: 4 months ago

pypi.org: mlflow-no-ssl

MLflow is an open source platform for the complete machine learning lifecycle

Documentation: https://mlflow-no-ssl.readthedocs.io/
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Latest release: 2.16.3
published over 1 year ago

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repo1.maven.org: org.mlflow:mlflow-spark_2.13

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-spark_2.13/
License: The Apache License, Version 2.0
Latest release: 3.3.2
published 4 months ago

Versions: 51
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Dependent repos count: 34.2%

Average: 41.5%

Dependent packages count: 48.8%

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repo1.maven.org: org.mlflow:mlflow-spark_2.12

Open source platform for the machine learning lifecycle

Homepage: http://mlflow.org
Documentation: https://appdoc.app/artifact/org.mlflow/mlflow-spark_2.12/
License: The Apache License, Version 2.0
Latest release: 3.3.2
published 4 months ago

Versions: 51
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent repos count: 34.2%

Average: 41.5%

Dependent packages count: 48.8%

Last synced: 4 months ago