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Paperback. Zustand: New. Scala as a programming language is a highly scalable integration of object-oriented and functional programming, which makes it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to train effective machine learning models using this popular language.…

paperback. Zustand: Very Good. Deep Learning with TensorFlow: Explore neural networks with Python This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .…

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Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

paperback. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

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Digital. Zustand: New. One stop guide to implementing award-winning, and cutting-edge CNN architecturesAbout This Book. Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques. Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more. Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention modelsWho This Book Is ForThis book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.What You Will Learn. From CNN basic building blocks to advanced concepts understand practical areas they can be applied to. Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it. Learn different algorithms that can be applied to Object Detection, and Instance Segmentation . Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy. Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more. Understand the working of generative adversarial networks and how it can create new, unseen imagesIn DetailConvolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available.Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.Style and approachAn easy to follow concise and illustrative guide explaining the core concepts of ConvNets to help you understand, implement and deploy your CNN models quickly. …

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Digital. Zustand: New. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.About This Book. Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow. Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide. Gain real-world contextualization through some deep learning problems concerning research and applicationWho This Book Is ForThe book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.What You Will Learn. Apply deep machine intelligence and GPU computing with TensorFlow. Access public datasets and use TensorFlow to load, process, and transform the data. Discover how to use the high-level TensorFlow API to build more powerful applications. Use deep learning for scalable object detection and mobile computing. Train machines quickly to learn from data by exploring reinforcement learning techniques. Explore active areas of deep learning research and applicationsIn DetailDeep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries.Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.Style and approachThis step-by-step guide explores common, and not so common, deep neural networks, and shows how they can be exploited in the real world with complex raw data. Benefit from practical examples, and learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.…

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Paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Digital. Zustand: New. Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.About This Book. Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j . Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way. Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework.Who This Book Is ForIf you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful.What You Will Learn. Apply advanced regression techniques to boost the performance of predictive models. Use different classification algorithms for business analytics . Generate trading strategies for Bitcoin and stock trading using ensemble techniques. Train Deep Neural Networks (DNN) using H2O and Spark ML. Utilize NLP to build scalable machine learning models . Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application. Learn how to use autoencoders to develop a fraud detection application. Implement LSTM and CNN models using DeepLearning4j and MXNetIn DetailMachine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet.At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.Style and approachLeverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.…

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

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