This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based ...

NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results"To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals."-- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA"Ekman uses a learning technique that in our e...

The book ‘Learn AI with Python’ is intended to provide you with a thorough understanding of artificial intelligence as well as the tools necessary to create your intelligent applications.This book introduces you to artificial intelligence and walks you through the process of establishing an AI environment on a variety of platforms. It dives into machine learning models and various predictive modeling techniques, including classification, regression, and clustering. Additionally, it provide...

Tackle the real-world complexities of modern machine learning with innovative, cutting-edge techniquesKey Features\[\*\]Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark\[\*\]Comprehensive practical solutions taking you into the future of machine learning\[\*\]Go a step further and integrate your machine learning projects with HadoopBook DescriptionT...

Your one-stop guide to becoming a Machine Learning expert.Key Features-Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning- A highly practical guide explaining the concepts of problem solving in the easiest possible manner- Implement Machine Learning in the most practical wayBook DescriptionMost of us have heard about the term Machine Learning, but surprisingly the question freq...

Model-Based Systems Engineering (MBSE), which tackles architecting and design of complex systems through the use of formal models, is emerging as the most critical component of systems engineering. This textbook specifies the two leading conceptual modeling languages, OPM—the new ISO 19450, composed primarily by the author of this book, and OMG SysML. It provides essential insights into a domain-independent, discipline-crossing methodology of developing or researching complex systems of an...

Build next-generation Artificial Intelligence systems with JavaKey FeaturesImplement AI techniques to build smart applications using Deeplearning4jPerform big data analytics to derive quality insights using Spark MLlibCreate self-learning systems using neural networks, NLP, and reinforcement learningBook DescriptionIn this age of big data, companies have larger amount of consumer data than ever before, far more than what the ...

Deep learning helps you solve issues related to data problems as it has a vast array of mathematical algorithms and has capacity to detect patterns.This book starts with a quick view of deep learning in Python which would include definition, features and applications. You would be learning about perceptron, neural networks, Backpropagation. This book would also give you a clear insight of how to use Numpy and Matplotlin in deep learning models. By the end of the book, you’ll have the knowl...

Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends on social networking sites to medical diagnosis and even satellite processing. In this book, we have made an honest effort to make the concepts of machine learning easy and give basic programs in MATLAB right from the installation part. Although ...

The book offers the readers the fundamental concepts of Machine Learning techniques in a user-friendly language. The book aims to give in-depth knowledge of the different Machine Learning (ML) algorithms and the practical implementation of the various ML approaches.This book covers different Supervised Machine Learning algorithms such as Linear Regression Model, Naïve Bayes classifier Decision Tree, K-nearest neighbor, Logistic Regression, Support Vector Machine, Random forest algorithms, ...

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statisti...

Get to grips with the essentials of deep learning by leveraging the power of PythonKey FeaturesYour one-stop solution to get started with the essentials of deep learning and neural network modelingTrain different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and moreCovers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deployin...