In 2011, Marc Andreessen famously said “Software is eating the world”. In 2022, Machine Learning (ML) and Data Science (DS) are devouring it. Robotics, consumer products, transportation, healthcare, etc.; every branch of the economy increasingly uses data to collect insights and make decisions and predictions.
As this revolution happens, the workforce is growing stronger every year with new engineers, scientists, and developers. And yet, the tools currently available to prototype and productionize models are not catching up. They are either too hard to adopt, too generic, too constraining, require too much infrastructure skills, or simply not useful or usable.
Tools such as Ruby on Rails and Heroku enabled generations of web developers to build prototypes into unicorns. Where is that experience for ML/DS development?
Sematic is an open-source framework to build and execute Machine Learning and Data Science pipelines.
With easy-as-pie onboarding, Sematic enables ML/DS developers to prototype and productionize pipelines faster in order to focus on data and model insights instead of wasting time on complex infrastructure.
Drawing from years of experience in academia and industry (CERN, Instacart, Cruise), Sematic aims to bring to ML/DS developers an experience that is both delightful and powerful by helping them turn rough Notebook prototypes into fully automated Continuous Learning Machines without the need for extensive infrastructure knowledge, in order to keep models fresh, safe, and relevant as world condition evolve.
We are excited to show you what Sematic can do.
Check out Sematic at sematic.dev and join us on Discord.