ML Ops in Production

<p class="p1"><span class="s1">Moses Guttman from Clear ML joins us to share insights about how organizations leveraging machine learning keep their programs on track.<span class= "Apple-converted-space"> </span> While<span class= "Apple-converted-space"> </span></span><span class="s1">many parallels exist between the software development life cycle (SWLC) and the machine learning development life cycle, successful deployments of ML in production<span class= "Apple-converted-space"> </span></span><span class="s1">have demonstrated that a unique set of tools is required.<span class= "Apple-converted-space"> </span> Moses and I discuss the emergence of ML Ops, success stories, and how modern teams leverage tools like<span class= "Apple-converted-space"> </span></span><span class="s1">Clear ML's open source solution to maximize the value of ML in the organization.</span></p> <p class="p1"> </p>