Introducing Studio.ML: Simplifying ML Model Development

Oct 12, 2017 · San Francisco, United States of America is an early-stage, ML model management framework written in Python and developed to minimize the overhead involved with scheduling, running, monitoring and managing artifacts of your machine learning experiments. 

Most of the features are compatible with any Python ML framework, including Keras, TensorFlow, PyTorch, and scikit-learn (additional features available for Keras and TensorFlow). This code is still in the early phases of development, but we want to share our work and encourage developers to try it, report back problems, ask questions, provide feedback and contribute.

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