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Artificial Intelligence By Example: Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition
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- Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examplesKey FeaturesAI-based examples to guide you in designing and implementing machine intelligence Build machine intelligence from scratch using artificial intelligence examples Develop machine intelligence from scratch using real artificial intelligenceBook DescriptionAI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google Translate Understand chained algorithms combining unsupervised learning with decision trees Solve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graph Learn about meta learning models with hybrid neural networks Create a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data logging Building conversational user interfaces (CUI) for chatbots Writing genetic algorithms that optimize deep learning neural networks Build quantum computing circuitsWho this book is forDevelopers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.Table of ContentsGetting Started with Next-Generation Artificial Intelligence through Reinforcement LearningBuilding a Reward Matrix Designing Your DatasetsMachine Intelligence Evaluation Functions and Numerical ConvergenceOptimizing Your Solutions with K-Means ClusteringHow to Use Decision Trees to Enhance K-Means ClusteringInnovating AI with Google TranslateOptimizing Blockchains with Naive BayesSolving the XOR Problem with a FNNAbstract Image Classification with CNNConceptual Representation LearningCombining RL and DLAI and the IoTVisualizing Networks with TensorFlow 2.x and TensorBoardPreparing the Input of Chatbots with RBMs and PCASetting Up a Cognitive NLP UI/CUI ChatbotImproving the Emotional Intelligence Deficiencies of ChatbotsGenetic Algorithms in Hybrid Neural NetworksNeuromorphic ComputingQuantum Computing
| Publisher | Packt Publishing |
| Publication date | February 28, 2020 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 578 pages |
| ISBN-10 | 1839211539 |
| ISBN-13 | 978-1839211539 |
| Item Weight | 2.38 pounds (1.08 kg) |
| Dimensions | 7.5 x 1.31 x 9.25 inches (19.1 x 3.3 x 23.5 cm) |
Hvem bør købe?
-
Aspiring Data Scientists
Ideal for individuals starting their journey into data science, seeking practical examples and hands-on experience with AI.
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AI Practitioners
Beneficial for experienced professionals looking to expand their knowledge in machine learning and deep learning techniques.
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Students of AI
Great resource for university students studying artificial intelligence, providing real-world applications and coding examples.
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Beginners in Tech
Not suitable for complete novices in technology, as some prior knowledge of programming and AI concepts is essential.
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Intelligence & Semantics Editorial Review
Artificial Intelligence By Example is an excellent resource for anyone looking to acquire advanced AI, machine learning, and deep learning design skills. The 2nd Edition builds upon the success of the first edition with updated content and new examples. The book provides a comprehensive and practical approach to understanding AI concepts and implementing them in real-world scenarios. The author's expertise shines through in the clear explanations and well-structured code samples. Whether you are a beginner or an experienced AI practitioner, this book will help you expand your knowledge and improve your AI skills.
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- Comprehensive and practical approach to understanding AI concepts
- Clear explanations and well-structured code samples
- Suitable for both beginners and experienced AI practitioners
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Egenskaber og fordele
- Understand AI theories, machine learning, deep learning, and major AI algorithms
- Get insights into e-commerce stages, IoT, open-source Python programs, cloud platforms, chatbots, and quantum computing
- Become a knowledgeable and creative AI specialist after finishing the book
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