Build a Machine Learning Model with Transparency

Building a machine learning model is complex, and you often end up with an unexplainable black box. PerceptiLabs is a visual modeling tool to build, train and tune your model, with a portal to actually see how your model works. Join us to see: - The transparency you get with PerceptiLabs model management platform to quickly understand what your model is doing, tune it, and keep track of the experiments. - How to seamlessly run ML jobs on any cloud/server while Red Hat takes care of the infrastructure for you. - A demo of Object Detection and how easy it is to build a model with a drag and drop tool. PerceptiLabs, a startup focused on making machine learning easy, created a flexible machine learning platform that gives developers full transparency into the process of machine learning models’ development. About the speaker: Martin Isaksson received his M.Sc. in Robotics/Artificial Intelligence from the Royal Institute of Technology and UPC Barcelona in 2017. His favorite model is a Deep Neural Network he built for segmentation of muscular stem cells in microscopy images. This webinar is co-hosted in partnership with Perceptilabs and Red Hat. As a result, both Red Hat and PerceptiLabs are collecting your personal data when you submit such information as part of the registration process above. For more information on each party’s privacy practices, please see: Red Hat’s Privacy Statement: www.redhat.com/en/about/privacy-policy PerceptiLabs privacy policy: https://www.perceptilabs.com/privacy_policy