Quantum Neural Computation is a graduate-level monographic textbook. It presents a comprehensive introduction, both non-technical and technical, into modern quantum neural computation. Classical computing systems perform classical computations (i.e., Boolean operations, such as …
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to t…
DEEP LEARNINGA concise and practical exploration of key topics and applications in data scienceIn Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big…
"This book comprehensively covers concepts of recurrent neural networks and discusses practical issues such as predictability and nonlinearity detecting. It will an ideal text for senior undergraduate, graduate students, researchers, and professionals in the fields of electrical…
This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describestheir tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product develo…
Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Dee…
Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques …
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Natural Language Processing with Java will explore how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. You will leverage the power of Java to extract relationships …
Packed with intriguing real-world projects as well as theory, Generative AI with Python and TensorFlow 2 enables you to leverage artificial intelligence creatively and generate human-like data in the form of speech, text, images, and music.
"Revolutionary and original, this treatise presents a new paradigm of EMERGENCE and COMPLEXITY, with applications drawn from numerous disciplines, including artificial life, biology, chemistry, computation, physics, image processing, information science, etc. CNN is an acronym f…
The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While …
Chapter 2: Data Exploration; An overview; Feature identification; The curse of dimensionality; Feature selection and feature extraction; Pearson correlation example; Cleaning and preparing data; Handling missing data; Missing categorical data; Missing numerical data; Handling no…
