Practical TensorFlow.js deep learning in web app development
Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow. js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard , ml5js , tfjs-vis. This book will cover all these technologies and show they integrate with TensorFl...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Apress
[2020]
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| Edición: | 1st ed. 2020. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630936606719 |
Tabla de Contenidos:
- Chapter 1: Welcome to TensorFlow.js
- Chapter 2: Training Our First Models
- Chapter 3: Doing k-means with ml5.js
- Chapter 4: Recognizing Handwritten Digits with Convolutional Neural Networks
- Chapter 5: Making a Game with PoseNet, a Pose Estimator Model
- Chapter 6: Identifying Toxic Text from a Google Chrome Extension
- Chapter 7: Object Detection with a Model Trained in Google Cloud AutoML
- Chapter 8: Training an Image Classifier with Transfer Learning on Node.js
- Chapter 9: Time Series Forecasting and Text Generation with Recurrent Neural Networks
- Chapter 10: Generating Handwritten Digits with Generative Adversarial Networks
- Chapter 11: Things to Remember, What's Next for You, and Final Words
- Appendix A: Apache License 2.0.
