Dive deeper into neural networks and get your models trained, optimized with this quick reference guideKey Features\[\*\]A quick reference to all important deep learning concepts and their implement……続きを見る
Build next-generation Artificial Intelligence systems with JavaKey FeaturesImplement AI techniques to build smart applications using Deeplearning4jPerform big data analytics to derive quality insigh……続きを見る
Leverage the power of reinforcement learning techniques to develop self-learning systems using TensorFlowKey Features\* Explore reinforcement learning concepts and their implementation using TensorF……続きを見る
Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key FeaturesImplement effective machine learning solutions for your iOS applicationsUse S……続きを見る
Edith Zeile, Jahrgang 1936, studierte Anglistik in Heidelberg und London und lehrte am Institut für Deutsch als Fremdsprachenphilologie der Universität und an der Universität Pittsburgh, USA. Schon ……続きを見る
Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engin……続きを見る
A hands-on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesYour entry point into the world of artificial intelligence using the power of PythonAn……続きを見る
Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using PythonKey FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world proje……続きを見る
Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calcu……続きを見る
Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for dat……続きを見る
This book provides different mathematical frameworks for addressing supervised learning. It is based on a workshop held under the auspices of the Center for Nonlinear Studies at Los Alamos and the S……続きを見る
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of probl……続きを見る
Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or n……続きを見る
Based upon a conference held in May 1993, this book discusses the intersection of neurobiology, cognitive psychology and computational approaches to cognition.
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The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial I……続きを見る
Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystemKey FeaturesBuild deep learning models with transfer learning prin……続きを見る
Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key FeaturesLearn how to implement advanced techniques in deep lea……続きを見る
This book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information i……続きを見る
Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with easeKey FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI……続きを見る
Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulatorKey FeaturesExpl……続きを見る
Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearnKey FeaturesBuild a variety of Hidden Markov Models (HMM)Create and apply models to an……続きを見る
I computer odierni sono così tanto intelligenti da essere più bravi di noi in una partita a scacchi o nel giocare ad un videogame. Ma essi sanno di essere così intelligenti? Hanno coscienza di sé e ……続きを見る
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlowKey FeaturesWeave neural networks into linguistic applications across various platformsPerform NLP tasks and train it……続きを見る
Work through exciting projects to explore the capabilities of Go and Machine LearningKey FeaturesExplore ML tasks and Go’s machine learning ecosystemImplement clustering, regression, classification,……続きを見る
Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handb……続きを見る
Leverage the power of Apple\\'s Core ML to create smart iOS appsKey Features\[\*\] Explore the concepts of machine learning and Apple’s Core ML APIs\[\*\] Use Core ML to understand and transform ima……続きを見る
Are you thinking of learning more about Machine Learning using R?
The overall aim of this book is to give you an overview of the data science applications using R.
Data science is the practice of tr……続きを見る
Be an adaptive thinker that leads the way to Artificial IntelligenceKey FeaturesAI-based examples to guide you in designing and implementing machine intelligenceDevelop your own method for future AI……続きを見る
