Difference between revisions of "MLflow"
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| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
| − | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | + | |
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[http://www.youtube.com/results?search_query=MLflow Youtube search...] | [http://www.youtube.com/results?search_query=MLflow Youtube search...] | ||
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* [http://mlflow.org/ MLflow.org] | * [http://mlflow.org/ MLflow.org] | ||
* [http://github.com/mlflow/mlflow MLflow | GitHub] | * [http://github.com/mlflow/mlflow MLflow | GitHub] | ||
| + | * [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]] | ||
| + | * [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]] | ||
| + | * [http://towardsdatascience.com/empowering-spark-with-mlflow-58e6eb5d85e8 Empowering Spark with MLflow | Albert Franzi - Towards Data Science] | ||
| + | * [http://www.kdnuggets.com/2018/07/manage-machine-learning-lifecycle-mlflow.html Manage your Machine Learning Lifecycle with MLflow] | ||
| + | * [[Databricks]] | ||
| − | MLflow is an open source platform | + | MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility and deployment. It currently offers three components:: |
| − | |||
| − | + | #Tracking — Record and query experiments: code, data, config, and results. | |
| + | #Projects — Packaging format for reproducible runs on any platform. | ||
| + | #Models — General format for sending models to diverse deployment tools. | ||
<youtube>wb-ZxtIwSTA</youtube> | <youtube>wb-ZxtIwSTA</youtube> | ||
<youtube>ek4mJnDw8eE</youtube> | <youtube>ek4mJnDw8eE</youtube> | ||
| + | |||
| + | http://developer.ibm.com/v1/AUTH_7046a6f4-79b7-4c6c-bdb7-6f68e920f6e5/Code-Articles/first-impressions-mlflow/images/mlflowObjects.jpg | ||
Latest revision as of 20:51, 26 April 2024
Youtube search... ...Google search
- MLflow.org
- MLflow | GitHub
- Analytics ... Visualization ... Graphical Tools ... Diagrams & Business Analysis ... Requirements ... Loop ... Bayes ... Network Pattern
- Development ... Notebooks ... AI Pair Programming ... Codeless ... Hugging Face ... AIOps/MLOps ... AIaaS/MLaaS
- Empowering Spark with MLflow | Albert Franzi - Towards Data Science
- Manage your Machine Learning Lifecycle with MLflow
- Databricks
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility and deployment. It currently offers three components::
- Tracking — Record and query experiments: code, data, config, and results.
- Projects — Packaging format for reproducible runs on any platform.
- Models — General format for sending models to diverse deployment tools.
