Production-ready applied deep learning learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks
While there are many books on various deep learning models, it is difficult to find a book about serving the models at scale. In this book, you will learn how to quickly build working models, convert them into production-ready applications supporting various deployment environments, and distribute t...
| Otros Autores: | , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England ; Mumbai :
Packt
[2022]
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009676325206719 |
Tabla de Contenidos:
- Table of Contents Effective Planning of Deep Learning-Driven Projects Data Preparation for Deep Learning Projects Developing a Powerful Deep Learning Model Experiment Tracking, Model Management, and Dataset Versioning Data Preparation in the Cloud Efficient Model Training Revealing the Secret of Deep Learning Models Simplifying Deep Learning Model Deployment Scaling a Deep Learning Pipeline Improving Inference Efficiency Deep Learning on Mobile Devices Monitoring Deep Learning Endpoints in Production Reviewing the Completed Deep Learning Project.
