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Transform Process in ML - Python for Integrated Circuits - - An Online Book - |
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| Python for Integrated Circuits 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 | ||||||||
================================================================================= Transform process in machine learning typically refers to the process of transforming raw input data into a format that is suitable for training a machine learning model or making predictions. This transformation can involve various preprocessing steps such as scaling, normalization, encoding categorical variables, feature engineering, and more. The goal is to prepare the data in a way that makes it easier for the machine learning algorithm to learn patterns and make accurate predictions.
Figure 4114. Vertex AI providing a unified set of APIs for the ML lifecycle. [1]
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[1] Diagram courtesy Henry Tappen and Brian Kobashikawa.
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