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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework

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Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet

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Deep Learning with PyTorch. A practical approach to building neural network models using PyTorch

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Deep Learning with PyTorch Lightning. Swiftly build high-performance Artificial Intelligence (AI) models using Python

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Deep Learning with PyTorch Quick Start Guide. Learn to train and deploy neural network models in Python

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Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x

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Deep Learning with R for Beginners. Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet

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Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition

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Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition

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Deep Learning with TensorFlow. Explore neural networks and build intelligent systems with Python - Second Edition

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Deep Learning with TensorFlow. Explore neural networks with Python

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Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently

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Deep learning z TensorFlow 2 i Keras dla zaawansowanych. Sieci GAN i VAE, deep RL, uczenie nienadzorowane, wykrywanie i segmentacja obiektów i nie tylko. Wydanie II

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Deep Reinforcement Learning Hands-On. Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

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Democratizing Application Development with Betty Blocks. Build powerful applications that impact business immediately with no-code app development

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