Getting to Ground Truth with Strategies from ML in Electronics Manufacturing (Alon Malki, Senior Director of Data Science, NI)

<p>Many people assume that once you establish a manufacturing line, the hard work is done and things remain relatively static. The reality, especially in electronics manufacturing, is entirely different.</p> <p>Constantly changing data streams and endlessly dynamic variables present some unique challenges for data scientists in the field. But there are lessons on data sharing, model adoption, and real-time impact that ML professionals in any field can learn from.</p> <p>In this episode, <a href="https://www.linkedin.com/in/alon-malki-1a567a46/"><ins>Alon Malki</ins></a>, Senior Director of Data Science at <a href="https://www.ni.com/"><ins>NI (National Instruments)</ins></a>, opens a window into the world of data science in electronics manufacturing. Plus, he shares why human-in-the-loop processes are essential to gaining buy-in for AI in the enterprise.</p> <p>We discuss:</p> <ul><li>Data science in electronics manufacturing</li> <li>Strategies for sharing data to improve manufacturing processes</li> <li>Human-in-the-loop applications</li> <li>Looking for challenge-motivated data science talent </li> </ul> <p><em>Tune in on </em><a href="https://podcasts.apple.com/us/podcast/data-science-leaders/id1564587119"><em><ins>Apple Podcasts</ins></em></a><em>, </em><a href="https://open.spotify.com/show/0zJgKGIHZzJG1VgSDHNojP"><em><ins>Spotify</ins></em></a><em>, our </em><a href="https://www.dominodatalab.com/data-science-leaders-podcast/"><em><ins>website</ins></em></a><em>, or wherever you listen to podcasts.</em></p> <p><em>Can’t see the links above? Just visit </em><a href="http://domino.buzz/podcast"><em><ins>domino.buzz/podcast</ins></em></a><em> for helpful links from each episode.</em></p>