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Kubeflow

Machine Learning Toolkit for Kubernetes
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What is 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.
Kubeflow is a tool in the Machine Learning Tools category of a tech stack.
Kubeflow is an open source tool with 8K GitHub stars and 1.2K GitHub forks. Here’s a link to Kubeflow's open source repository on GitHub

Who uses Kubeflow?

Companies
5 companies reportedly use Kubeflow in their tech stacks, including data-science, Hepsiburada, and bigin.

Developers
14 developers on StackShare have stated that they use Kubeflow.

Kubeflow Integrations

Kubernetes, Jupyter, TensorFlow, Pipelines, and Google AI Platform are some of the popular tools that integrate with Kubeflow. Here's a list of all 5 tools that integrate with Kubeflow.

Why developers like Kubeflow?

Here’s a list of reasons why companies and developers use Kubeflow
Top Reasons
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Kubeflow Alternatives & Comparisons

What are some alternatives to Kubeflow?
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.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
MLflow
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
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.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
See all alternatives

Kubeflow's Followers
30 developers follow Kubeflow to keep up with related blogs and decisions.
Klas Kalaß
frank zeng
arunadfolks
Josiah Clark
Himansu Sekhar
Jin Chen
Mohamma76685757
Eli Perl
AlirezaSadeghi
Travis Gray