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Deploying 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 | ||||||||
================================================================================= Sequential API can be used to create a Keras model with TensorFlow (e.g. on Vertex AI platform). Then, the Keras Sequential API and Feature Columns can be used to build deep neural network (DNN). In combination with a trained model, the Keras model can be saved, loaded and deployed, and then the model can be called for making predictions.
Figure 4114. Vertex AI providing a unified set of APIs for the ML lifecycle. [1] On Google Console, this deploying and predicting processes can be done with the trained model using Cloud AI Platform. ============================================
[1] Diagram courtesy Henry Tappen and Brian Kobashikawa.
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