2nd Edition. — Packt Publishing, 2020. — 512 p. — ISBN: 978-1-83882-165-4. Code files only! Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available...
Packt Publishing, 2020. — 286 p. — ISBN: 978-1-78913-396-7. Code files only! Work through practical recipes to learn how to automate complex machine learning and deep learning problems using Python. With artificial intelligence systems, we can develop goal-driven agents to automate problem-solving. This involves predicting and classifying the available data and training agents...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Code files only! Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent...
Packt Publishing, 2018. — 272 p. — ISBN: 1788837991. Dive deeper into neural networks and get your models trained, optimized with this quick reference guide. Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It...
Apress, 2017. — 227 p. — ISBN: 978-1484227336. Code files only! Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R...
Manning Publications, 2020. — 560 p. — ISBN: 978-1-617296-17-8. Code files only! Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL...
Packt Publishing, 2018. — 334 p. Code files only! A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who dont have a data science background Covers the key foundational concepts youll need to know when building deep learning systems Full of...
Packt, 2019. — 612 p. — ISBN: 9781838642709. !Code files only Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the fundamentals of deep learning and neural networks Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing Implement effective deep...
Packt Publishing, 2020. — 145 p. — ISBN: 978-1-83882-546-1. Code files only! Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there...
2nd edition. — Apress, 2021. — 316 p. — ISBN 978-1484253632. Code files only! Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Code files only! Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of...
Packt Publishing Ltd., 2019. — 303 p. — ISBN: 978-1-78899-808-6. Code files only! Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help...
Packt Publishing, 2020. — 384 p. — ISBN 978-1-80056-661-3. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key Features - Become well-versed with KNIME Analytics Platform to perform codeless deep learning - Design and build deep learning workflows quickly and more easily using the KNIME GUI -...
Apress, 2018. — 425 p. — ISBN: 1484237897. Code files only! Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid,...
2nd Edition. — Packt Publishing, 2020. — 444 p. — ISBN: 978-1-83921-757-9. Code files only! Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming You already know that you want to learn Keras, and a smarter way to learn is to learn by doing. The Deep Learning with Keras Workshop focuses on building up your...
Fullstack.io, 2020. — 769 p. Code files only! Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of...
Apress, 2018. — 290 p. — ISBN: 148423684X. Code files only! Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. Code files only! You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine...
Packt Publishing, 2020. — 294 p. — ISBN: 978-1-78899-520-7. Code files only! Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy....
Manning Publications, 2020. — 266 p.— ISBN 1617296724, 9781617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you’ll find in the relational databases that real-world...
Apress, 2021. — 394 p. — ISBN 978-1484268087. Source Code only! Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing...
Packt Publishing, 2019. — 228 p. — ISBN: 978-1-78934-099-0. Code files only! Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Packt Publishing, 2020. — 455 p. — ISBN: 978-1-78995-617-7. Code files only! Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN...
Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
Packt Publishing, 2016. — 170 p. + Code. — ISBN: 978-1-78528-058-0. Build automatic classification and prediction models using unsupervised learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430 !Code files only Deep Reinforcement Learning in Action teaches you how to program agents that learn and improve based on direct feedback from their environment. You’ll build networks with the popular PyTorch deep learning framework to explore reinforcement learning algorithms ranging from Deep Q-Networks to Policy...
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