Spell is an end-to-end data science and machine learning platform that provides the infrastructure for companies and developers to prepare, train, deploy, and manage the full lifecycle of Machine Learning and Deep Learning experiments.
Spell is a platform for Machine Learning and Deep Learning for those looking to run multiple experiments in parallel and get fast results without worrying about overhead or infrastructure management.
Spell is built for Team collaboration, project monitoring, and experiment reproduction. The platform’s Jupyter workspaces, datasets, and resources are straightforward and accessible. Spell’s clear and concise flow also makes it easy to onboard new hires and get them up and running quickly.
Spell’s white glove service features on-premise deployment and real-time Slack support. Companies can work on their specific operations. The platform integrates with Single-Sign-on systems, internal data stores, and governance systems. This premium service provides everything necessary for clients to be successful in their Machine Learning and Deep Learning endeavors.
Don’t be held back by infrastructure. Access the fastest CPU and GPU machine types and frameworks in seconds.
Easily distribute your code to run projects in parallel. Built-in hyperparameter optimization tools, and integrations with Tensorboard and Weights & Biases help improve models up to 10x faster.
Deploy easily to your private cloud and quickly start machine learning projects. Bring your own AWS or GCP credits, keep data in your S3 or Google Cloud buckets, and deploy models within your private cloud infrastructure.
Deploy models in one-click on industrial-grade, auto-scaling, Kubernetes-based infrastructure. Easily manage the model life cycle, model versions, and performance results of inference.
Take control of your projects from start to finish. Our Workflow API and Metrics API allow you to automate key stages in your ML pipeline. Create charts to track the performance of your code.
See some of their testimonials here
I had the opportunity to work with Spell on a challenge for Omdena to preprocessing our datasets. This was a great experience because on my laptop this process took many hours while on Spell it was much faster and my laptop didn't freeze. Additionally, Spell had logs where I can monitor my process, kill the run if it is necessary, and I can see how long the run is so I can monitor performance in my code.
Spell is a collaborative platform that lets anyone run machine learning experiments.
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