<a href="http://meet.meetup.com/wf/click?upn=DtKvkirJMjJK-2FpI8UHiQTj9xnStKDsZSBFsp528SQSE-3D_4Mb6KtWrDXK23iA6C-2F1JqQ6tgeAjd9SG8SEZyCZcH5wM-2BXHOYbfhUmzHYglsSESggMSc2DS3SjeBx-2BC96IjOXliD6t5odjuKI49xE-2BY3Y3AxPdBln4yJ3C5OqQI7j5HP2SkyUmdEng1hZRivnAfZpNkE32tpjqWIjBjUB6zHs7v-2BZCnRe2xDX88RrK9CoO-2FcVkwKmxGjZcpph5VMFfTn-2FA-3D-3D">Studio.ml is an open source project dedicated to helping machine learning (ML) professionals, academics, businesses and anyone else interested in ML model building, accelerate and simplify their experiments.
Studio.ml is an early-stage, ML model management framework written in Python that was developed to minimize the overhead involved with scheduling, running, monitoring and managing artifacts of your machine learning experiments.
So far, using Studio.ml you can:
Capture experiment information- Python environment, files, dependencies and logs- without modifying the experiment code
Monitor and organize experiments using a web dashboard that integrates with TensorBoard
Perform hyperparameter search
Create customizable Python environments for remote execution
Access the model library to reuse models that have already been created
Peter Zhokhov is a Senior Software Engineer in the Sentient core platform group. He has a PhD in Physics from Texas A&M.