Search Results for Wish - Narrowed by: Machine learning

Hands-on deep learning with Go : a practical guide to building and implementing neural network models using Go / Gareth Seneque, Darrell Chua.

2024-05-18T12:57:08Z

by Seneque, Gareth, author.
Call Number 006.31 23
Publication Date 2019
Summary The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ...
Format: Electronic Resources
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Hands-on machine learning with scikit-learn and scientific Python toolkits : a practical guide to implementing supervised and unsupervised machine learning algorithms in Python / Tarek Amr.

2024-05-18T12:57:08Z

by Amr, Tarek, author.
Call Number 006.31 23
Publication Date 2020
Summary This book covers the theory and practice of building data-driven solutions. Includes the end-to-end process, using supervised and unsupervised algorithms. With each algorithm, you will learn the data acquisition and data engineering methods, the apt metrics, and the available hyper-parameters. You will learn how to deploy the models in production.
Format: Electronic Resources
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Deep Learning for Natural Language Processing : Solve Your Natural Language Processing Problems with Smart Deep Neural Networks.

2024-05-18T12:57:08Z

by Reddy Bokka, Karthiek.
Call Number 006.35 23
Publication Date 2019
Summary Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.
Format: Electronic Resources
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Python image processing cookbook : over 60 recipes to help you perform complex image processing and computer vision tasks with ease / Sandipan Dey.

2024-05-18T12:57:08Z

by Dey, Sandipan, author.
Call Number 005.133 23
Publication Date 2020
Format: Electronic Resources
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The the Deep Learning with Pytorch Workshop [electronic resource] : Build Deep Neural Networks and Artificial Intelligence Applications with Pytorch.

2024-05-18T12:57:08Z

by Saleh, Hyatt.
Call Number 006.31 23
Publication Date 2020
Summary With this hands-on, self-paced guide, you'll explore crucial deep learning topics and discover the structure and syntax of PyTorch. Challenging activities and interactive exercises will keep you motivated and encourage you to build intelligent applications effectively.
Format: Electronic Resources
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Hands-On Image Generation with TensorFlow : A practical guide to generating images and videos using deep learning / Soon Yau Cheong.

2024-05-18T12:57:08Z

by Cheong, Soon Yau, author.
Call Number 006.37 OCOLC 23ENG20230216
Publication Date 2020
Summary This book is a step-by-step guide to show you how to implement generative models in TensorFlow 2.x from scratch. You'll get to grips with the image generative technology by covering autoencoders, style transfer, and GANs as well as fundamental and state-of-the-art models.
Format: Electronic Resources
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Hands-On Generative Adversarial Networks with Pytorch 1. x : Implement Next-Generation Neural Networks to Build Powerful GAN Models Using Python.

2024-05-18T12:57:08Z

by Hany, John.
Call Number 005.133 23
Publication Date 2019
Summary This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective.
Format: Electronic Resources
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