ML Toolkit Aims to Ease Data Scientists’ Pain

As the AI services ecosystem expands, vendors are offering automation tools designed to make life easier for embattled data scientists through toolkits used to build machine and deep learning models, and then move those trained models to production.

That’s the premise behind the upgraded version of machine learning “lab” from toolkit vendor called Neptune. The AI startup based in Palo Alto, Calif., positions its toolkit as enabling data scientists to build machine-learning models in their preferred framework, including Keras, the open source neural network library, and TensorFlow, the Google-developed machine-learning framework.

Author: George Leopold


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