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MLflow

110
350
+ 1
6
Seldon

10
29
+ 1
0
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    What is MLflow?

    MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

    What is Seldon?

    Seldon is an Open Predictive Platform that currently allows recommendations to be generated based on structured historical data. It has a variety of algorithms to produce these recommendations and can report a variety of statistics.

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    What companies use MLflow?
    What companies use Seldon?
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    What tools integrate with MLflow?
    What tools integrate with Seldon?
      No integrations found
      What are some alternatives to MLflow and Seldon?
      Kubeflow
      The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
      Airflow
      Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
      TensorFlow
      TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
      DVC
      It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.
      Metaflow
      It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.
      See all alternatives