Showing results for "john hany"
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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
2019
EN
Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network modelsKey FeaturesImplement GAN architectures to generate images, text, audio, 3D models, and moreUnderstand how GANs work and become an active contributor in the open source communityLearn how to generate photo-realistic images based on text descriptionsBook DescriptionWith continuously evolving research and devel...
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Beautiful Code
Leading Programmers Explain How They Think
2007
EN
How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes.This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things....
Artificial Intelligence with Python
A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers
2017
EN
Publisher's Note: This edition from 2017 is outdated and not compatible with TensorFlow 2.x or any of the most recent updates to Python libraries. A new edition completely updated and revised for 2020 with seven additional chapters that cover RNNs, AI and big data, fundamental use cases, chatbots, and more, is now available. Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you. Key FeaturesStep int...
2020
EN
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embed...
Learning OpenCV 3 Computer Vision with Python (Update)
Unleash the power of computer vision with Python using OpenCV
2015
EN
Unleash the power of computer vision with Python using OpenCV Key FeaturesBook DescriptionOpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the dev...
Computer Science
An Interdisciplinary Approach
2016
EN
Named a Notable Book in the 21st Annual Best of Computing list by the ACM!Robert Sedgewick and Kevin Wayne’s Computer Science: An Interdisciplinary Approach is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing.The book de...
Learning OpenCV 4 Computer Vision with Python 3
Get to grips with tools, techniques, and algorithms for computer vision and machine learning
2020
EN
Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical codeKey FeaturesBuild powerful computer vision applications in concise code with OpenCV 4 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learni...
Introduction to Programming in Python
An Interdisciplinary Approach
2015
EN
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it.Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools n...
Deep Learning with TensorFlow 2 and Keras
Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API
2019
EN
Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devicesKey FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook DescriptionDeep Learning with TensorFlow 2 and ...
Deep Learning with Keras
Implementing deep learning models and neural networks with the power of Python
2017
EN
Get to grips with the basics of Keras to implement fast and efficient deep-learning modelsKey FeaturesImplement various deep learning algorithms in Keras and see how deep learning can be used in gamesSee how various deep learning models and practical use-cases can be implemented using KerasA practical, hands-on guide with real-world examples to give you a strong foundation in KerasBook DescriptionThis book starts by introduci...
2018
EN
Become a machine learning pro!Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book on the subject. Inside, you’ll find out how to write applications with TensorFlow, while also grasping the concepts underlying machine learning—all without ever losing your cool!
Hands-On Computer Vision with TensorFlow 2
Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras
2019
EN
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and moreKey FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performance











