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Las 11 mejores herramientas Open Source para Machine Learning

Os dejamos nuestra recopilación de las 11 mejores herrramientas Open Source, que si te dedicas al Machine Learning no debes dejar de conocer y usar:

  1. TensorFlow
TensorFlow
An end-to-end open source machine learning platform for everyone. Discover TensorFlow’s flexible ecosystem of tools, libraries and community resources.

2.   Scikit-learn

scikit-learn: machine learning in Python — scikit-learn 0.23.2 documentation

3.  PyTorch

PyTorch
An open source deep learning platform that provides a seamless path from research prototyping to production deployment.

4.  Weka

Weka 3 - Data Mining with Open Source Machine Learning Software in Java

5.  Spark MLib

MLlib | Apache Spark
MLlib is Apache Spark’s scalable machine learning library, with APIs in Java, Scala, Python, and R.

6.  H2O

Home - Open Source Leader in AI and ML
H2O.ai is the creator of H2O the leading open source machine learning and artificial intelligence platform trusted by data scientists across 14K enterprises globally. Our vision is to democratize intelligence for everyone with our award winning “AI to do AI” data science platform, Driverless AI.

7.  KNIME

KNIME | Open for Innovation

8. Neo4J

Neo4j Graph Platform – The Leader in Graph Databases
Neo4j is the graph database platform powering mission-critical enterprise applications like artificial intelligence, fraud detection and recommendations.

9. MLFlow

MLflow - A platform for the machine learning lifecycle
An open source platform for the end-to-end machine learning lifecycle

10. Keras

Keras: the Python deep learning API
Keras documentation

11. Rapid Miner

RapidMiner | Best Data Science & Machine Learning Platform
RapidMiner is a data science platform that unites data prep, machine learning & predictive model deployment. Depth for data scientists, simplified for everyone else.