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Practical Deep Learning for Cloud and Mobile RealWorld AI Computer Vision Projects Using Python, Keras TensorFlow

learning applications for the cloud and mobile using a hands-on approach. Relying on years of industry experience transforming deep-learning;

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Deep Learning Projects Using TensorFlow 2

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will;

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Deep Learning with TensorFlow 2 and Keras

learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow;

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Deep Learning with Python

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You'll learn directly;

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Deep Learning for Computer Vision

kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to;

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Mastering OpenCV 4 with Python

application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book;

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R Deep Learning Essentials

Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for;

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Advanced Deep Learning for Engineers and Scientists

effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python;

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Advanced Deep Learning with Keras

libraries. A new second edition, updated for 2020 and featuring TensorFlow 2 and coverage of unsupervised learning using mutual information, object;

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Deep Learning with Applications Using Python

Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and;

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Applied Reinforcement Learning with Python

Implement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras Deploy and train reinforcement;

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TensorFlow 2 Reinforcement Learning Cookbook

reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x. By the end of this TensorFlow book, you'll have;

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Computer Vision Projects with OpenCV and Python 3

Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major;

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The Deep Learning Workshop

Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;

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Hands-On Deep Learning for Images with TensorFlow

fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;

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Reinforcement Learning

learning and AI Work with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using Python Who This Book;

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Hands-On Computer Vision with TensorFlow 2

. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural;

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Deep Learning Essentials

Language Processing, computer vision, speech recognition, and more Covers popular Python libraries such as Tensorflow, Keras, and more, along with;

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Mastering Computer Vision with TensorFlow 2.x

learning and want to build expert-level computer vision applications. In addition to familiarity with TensorFlow, Python knowledge will be required;

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Step by Step Tutorials on Deep Learning Using Scikit-Learn, Keras, and Tensorflow with Python GUI

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Python Deep Learning

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book;

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Practical Explainable AI Using Python

AI models. Practical Explainable AI Using Python shines the light on deep learning models, rule-based expert systems, and computer vision;

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Practical Computer Vision Applications Using Deep Learning with CNNs

Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning;

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TensorFlow 2.0 Computer Vision Cookbook

machine learning and deep learning techniques Key Features Develop, train, and use deep learning algorithms for computer vision tasks using;

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AI and Machine Learning For Coders A Programmer's Guide to Artificial Intelligence

TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision;

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Deep Learning with Python

FEATURES * Practical code examples * In-depth introduction to Keras * Teaches the difference between Deep Learning and AI ABOUT THE;

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Applied Machine Learning for Health and Fitness

Explore the world of using machine learning methods with deep computer vision, sensors and data in sports, health and fitness and other;

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