Algorithmia – Machine Learning and Data Science
A recent 451 Research Voice of the Enterprise survey looked at the adoption of machine learning (ML) in the enterprise. ML is currently in use by 20% of enterprises, with a further 20% in the proof of concept stage. Additionally, the research mentions a further 21% are planning ML adoption within the next two years.
There is a clear level of interest in ML, and data science in general. However, there is less clarity in terms of how enterprises go about adopting ML. Also, around scaling data science experiments and turning them into production deployments.
In this podcast, Industry Analyst at 451 research, Matt Aslett speaks to Diego Oppenheimer, CEO of Algorithmia. They discuss how organisations are successfully adopting data science and machine learning. This includes the differences between the traditional software development life cycle and machine learning life cycle. Finally, they review some tactical and strategic challenges of operationalising machine learning.
Algorithmia invented the AI Layer. Our serverless infrastructure is custom built to host scalable AI models and advanced algorithms. Simply add your code and we’ll automatically generate API pipelines for hassle-free deployment and maintenance-free scalability. Any model you add can optionally be monetized in the marketplace. Today more than 55,000 developers have access to a growing library of 4,000 algorithmic microservices. Our team is dedicated to reaching developers on every corner of the earth, we hope you consider joining us.
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