New to Machine Learning? Check out learn.spell.ml
Streamline your projects with an end-to-end machine learning pipeline.
Spell is a powerful platform for building and managing machine learning projects. Spell takes care of infrastructure, making machine learning projects easier to start, faster to get results, more organized and safer than managing infrastructure on your own.
Built for team collaboration, project monitoring, and experiment reproducibility. Spell provides everything teams need to thrive and accelerate productivity, including collaborative Jupyter workspaces and resources.
Increase efficiency and monitor progress with a single platform that securely organizes projects, data, models, and results. View active runs, compare experiments, and monitor long-term results in the web console.
Save time on setup and management with Spell’s intuitive web console and simple command line tools.
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.
Run experiments on the best CPU or GPU machine types and frameworks without investing time and money into infrastructure and management. The Spell platform is intuitive, uses simple command line tools, and accessible through a web console.
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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