By Mercury Learning | in eBooks
This book lends insight into solving some well-known AI problems using the most efficient problem-solving methods by humans and computers. The book discusses the importance of developing critical-thinking methods and skills and develops a consistent approach toward each problem. This book assembles in one place a set of interesting and challenging AI–type problems that students regularly encounter in computer science, mathematics, and AI courses. The book is especially useful as a companion to any course in computer science or mathematics where there are interesting problems to solve.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Danny Kopec taught at Brooklyn College and the CUNY Graduate Center. He authored several books, conference and journal articles, and was an International Chess Master.
Christopher Pileggi holds a degree in Computer Information Science and is employed by the Center for Economic Workforce & Development.
David Ungar holds a degree in Computer Information Science.
By Mercury Learning | in eBooks
Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on Prolog and Python. The concluding chapter on artificial intelligence machines and robotics is comprehensive with numerous modern applications.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
N. Gupta, PhD teaches courses in artificial intelligence and specializes in expert systems.
R. Mangla is the proprietor of a large manufacturing company using AI machines.
By Mercury Learning | in eBooks
This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and autoencoders. Keras-based code samples are included to supplement the theoretical discussion. Besides, this book contains appendices for Keras, TensorFlow 2, and Pandas.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
By Mercury Learning | in eBooks
This text provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations. It includes numerous examples, applications, full-color images, and human interest boxes to enhance student interest. Advanced topics cover neural nets, genetic algorithms, and complex board games. A companion DVD is included with resources, simulations, and figures from the book. Instructors’ resources are available upon adoption.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Stephen Lucci holds a Ph.D. from the CUNY Graduate School and currently teaches computer science at The City College of New York. Dr. Lucci has published in the areas of high performance computing and artificial intelligence.
Danny Kopec holds a Ph.D. from the University of Edinburgh and currently teaches at Brooklyn College. He has authored several books and journal articles and is an International Chess Master.
By Mercury Learning | in eBooks
This book lends insight into solving some well-known AI problems using the most efficient methods by humans and computers. The book discusses the importance of developing critical-thinking methods and skills and develops a consistent approach toward each problem. This book covers some of the classic Ai problems such as Twelve Coins, Red Donkey, Cryptarithms, Rubik's Cube, and more. It includes a playability site where you can exercise the process of developing your solutions.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Danny Kopec taught at Brooklyn College and the CUNY Graduate Center. He authored several books, conference and journal articles, and was an International Chess Master.
Shweta Shetty is an SAP PI Consultant.
Christopher Pileggi holds a degree in Computer Information Science and is employed by the Center for Economic Workforce & Development.
By Mercury Learning | in eBooks
This book is designed to identify some of the current applications and techniques of artificial intelligence as an aid to solving problems and accomplishing tasks. It provides a general introduction to the various branches of AI which include formal logic, reasoning, knowledge engineering, expert systems, neural networks, and fuzzy logic, etc. The book has been structured into five parts with an emphasis on expert systems: problems and state-space search, knowledge engineering, neural networks, fuzzy logic, and Prolog.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
I. Gupta teaches courses in Artificial Intelligence and specializes in expert system research.
G. Nagpal teaches courses in Artificial Intelligence and specializes in expert system research.
By Mercury Learning | in eBooks
This book is an introduction to programming concepts that uses Python 3 as the target language. It follows a practical just-in-time presentation – the material is given to the student when it is needed. Many examples will be based on games because Python has become the language of choice for basic game development. Designed as a Year One textbook for an introduction to programming classes or for the hobbyist who wants to learn the fundamentals of programming, the text assumes no programming experience.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
James R. Parker, PhD is a professor of Art and Digital Media at the University of Calgary. His areas of research include computer games and media art, computer simulation, and educational technology. Dr. Parker is the author of several texts, including:Python: Introduction to Programming and Python 3 Pocket Primer.
By Mercury Learning | in eBooks
As part of the best-selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of Python 3 to be able to work on their own projects. In addition to covering all of the basic concepts, the book features a chapter on PyGame, which allows a programmer to handle graphics, mouse and keyboard interaction, and play sounds and videos. Companion files that accompany this book contain all of the code examples as complete working programs. This means that there is no need to key them in, so they can be executed and perhaps modified or expanded.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
James R. Parker, PhD is a professor of Art and Digital Media at the University of Calgary. His areas of research include computer games and media art, computer simulation, and educational technology. Dr. Parker is the author of several texts, including:Python: Introduction to Programming and Python 3 Pocket Primer.
By Mercury Learning | in eBooks
As part of the new Pocket Primer series, this book provides an overview of the major aspects and the source code to use Python 2. It covers the latest Python developments, built-in functions and custom classes, data visualization, graphics, databases, and more. It includes a companion disc with appendices, source code, and figures. This Pocket Primer is primarily for self-directed learners who want to learn Python 2 and it serves as a starting point for deeper exploration of Python programming.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
By Mercury Learning | in eBooks
This video series will provide the viewer with some basic programming skills in NumPy and Pandas. The package includes thirteen videos with detailed instructions using code samples. Topics range from Introduction to NumPy and Pandas to NumPy arrays, vectors and operators, Pandas Dataframes, operations, and more. A supplemental video on using Google Colaboratory is also included.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
By Mercury Learning | in eBooks
This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.
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Important Details
Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
By Mercury Learning | in eBooks
As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and sci-kit-learn. The final two chapters contain an assortment of TensorFlow 1.0x code samples, including detailed code samples for the TensorFlow Dataset (which is used heavily in TensorFlow 2 as well).
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Important Details
Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
By Mercury Learning | in eBooks
This book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in the industry. The book has been divided into four sections. The first section deals with the language fundamentals, primarily the procedural part of the language, the second introduces the object-oriented paradigms, the third section deals with data structures, and the last is devoted to advanced topics like handling multi-dimensional arrays using NumPy and visualization using Matplotlib. Regular expressions and multi-threading have been introduced in the appendices.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
H. Bhasin is a professional programmer, researcher, and the author of several books including: Programming in C#, Algorithm Analysis and Design, and Theory of Computation.
By Mercury Learning | in eBooks
This book will guide you through the basic game development process using Python, covering game topics including graphics, sound, artificial intelligence, animation, game engines, etc. Real games are created as you work through the text and significant parts of a game engine are built and made available for download. The companion disc contains all of the resources described in the book, e.g. example code, game assets, video/sound editing software, and color figures. Instructor resources are available for use as a textbook.
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Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
James R. Parker, PhD is a professor of Art and Digital Media at the University of Calgary. His areas of research include computer games and media art, computer simulation, and educational technology. Dr. Parker is the author of several texts, including:Python: Introduction to Programming and Python 3 Pocket Primer.
By Mercury Learning | in eBooks
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge.
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Important Details
Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).