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To predict the quality of Wafer Sensors .Consists of ML Models which predicts whether wafer is needed to be replaced or not. Model Selection for finding best model with accuracy . Deployed using Flask.

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Wafer-Fault-Detection

Wafer (In electronics), also called a slice or substrate, is a thin slice of semiconductor, such as a crystalline silicon (c-Si), used for fabrication of integrated circuits and in photovoltaics, to manufacture solar cells.

The inputs of various sensors for different wafers have been provided. The goal is to build a machine learning model which predicts whether a wafer needs to be replaced or not (i.e whether it is working or not) nased on the inputs from various sensors

There are two classes: +1 and -1: +1: Means that the wafer is in a working condition and it doesn't need to be replaced. -1: Means that the wafer is faulty and it needa to be replaced.

To predict the quality of Wafer Sensors. Consists of ML Models which predicts whether wafer is needed to be replaced or not. Model Selection for finding best model with accuracy . Deployed using Flask.

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To predict the quality of Wafer Sensors .Consists of ML Models which predicts whether wafer is needed to be replaced or not. Model Selection for finding best model with accuracy . Deployed using Flask.

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