MLflow

73
236
+ 1
3
Swift AI

11
31
+ 1
0
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MLflow vs Swift AI: What are the differences?

MLflow: An open source machine learning platform. MLflow is an open source platform for managing the end-to-end machine learning lifecycle; Swift AI: A.I. and machine learning library written in Swift. Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!.

MLflow and Swift AI can be primarily classified as "Machine Learning" tools.

MLflow and Swift AI are both open source tools. It seems that Swift AI with 5.58K GitHub stars and 542 forks on GitHub has more adoption than MLflow with 23 GitHub stars and 13 GitHub forks.

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Pros of Swift AI
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    What is MLflow?

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

    What is Swift AI?

    Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!
    What companies use MLflow?
    What companies use Swift AI?
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      What tools integrate with MLflow?
      What tools integrate with Swift AI?
      What are some alternatives to MLflow and Swift AI?
      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.
      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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