Andrés P. Torres 
Deep Learning with MXNet Cookbook [EPUB ebook] 
Discover an extensive collection of recipes for creating and implementing AI models on MXNet

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Explore the capabilities of the open-source deep learning framework MXNet to train and deploy neural network models and implement state-of-the-art (SOTA) architectures in Computer Vision, natural language processing, and more. The Deep Learning with MXNet Cookbook is your gateway to constructing fast and scalable deep learning solutions using Apache MXNet.
Starting with the different versions of MXNet, this book helps you choose the optimal version for your use and install your library. You’ll work with MXNet/Gluon libraries to solve classification and regression problems and gain insights into their inner workings. Venturing further, you’ll use MXNet to analyze toy datasets in the areas of numerical regression, data classification, picture classification, and text classification. From building and training deep-learning neural network architectures from scratch to delving into advanced concepts such as transfer learning, this book covers it all. You’ll master the construction and deployment of neural network architectures, including CNN, RNN, LSTMs, and Transformers, and integrate these models into your applications.
By the end of this deep learning book, you’ll wield the MXNet and Gluon libraries to expertly create and train deep learning networks using GPUs and deploy them in different environments.

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Sprache Englisch ● Format EPUB ● Seiten 370 ● ISBN 9781800562905 ● Dateigröße 17.2 MB ● Verlag Packt Publishing ● Land NZ ● Erscheinungsjahr 2023 ● herunterladbar 24 Monate ● Währung EUR ● ID 9296401 ● Kopierschutz ohne

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