Episode 40
Getting to Ground Truth with Strategies from ML in Electronics Manufacturing
Data Science Leaders | 26:29 | March 02, 2022
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.
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.
In this episode, Alon Malki, Senior Director of Data Science at NI (National Instruments), 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.
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.
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.
In this episode, Alon Malki, Senior Director of Data Science at NI (National Instruments), 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.
We discuss:
- Data science in electronics manufacturing
- Strategies for sharing data to improve manufacturing processes
- Human-in-the-loop applications
- Looking for challenge-motivated data science talent
