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Feature Engineering in Semiconductor Manufacturing ML - Python Automation and Machine Learning for ICs - - An Online Book: Python Automation and Machine Learning for ICs by Yougui Liao - |
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Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= Feature engineering is a critical role in enhancing defect detection processes through ML, focusing on the identification of key features that can predict wafer defects with high accuracy. For instance, you are the quality assurance manager at a semiconductor manufacturing company. Recently, you noticed an increase in defects in the wafers used for microchip production that need to be filtered out to maintain product quality. You want to use machine learning to predict which wafers are defective and should be rejected. Then, some possible features in this machine learning use case to detect defective wafers can be:
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