Machine learning (ML) tools are exploding and specializing, giving users the option to build and manage their ML models in different ways ranging from writing code, relying on frameworks to using automated solutions, each with their pros and cons. The good news is, PerceptiLabs has developed a next-generation ML tool
https://www.brighttalk.com/webinar/build-a-machine-learning-model-with-transparencyWe’re excited to announce we’ll be presenting a session at the upcoming Red Hat webinar series AI/ML: Smart apps, easy delivery, fast platform on Wednesday, June 17. This webinar series will provide a variety of perspectives on driving innovation by simplifying the
Digital systems are only useful if they can be trusted to do their job. With traditional deterministic systems, we could derive a degree of certainty that a system was working correctly through processes such as unit tests, end-user testing, code reviews, and design documentation. AI is inherently non-deterministic in nature,
Introducing PerceptiLabs, a Visual Modeling Tool for Machine Learning In the past four to five years, with the growth of machine learning (ML) we’ve seen the number of available ML frameworks explode. TensorFlow has become a prominent player, especially when paired with languages and frameworks like Python and NumPy.