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Use ensemble learning techniques and models to improve your machine learning results. Ensemble Learning for AI Developers starts you at;
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Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and;
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AI models. Practical Explainable AI Using Python shines the light on deep learning models, rule-based expert systems, and computer vision;
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simple business AI application. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI and;
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Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI;
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) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be;
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models using individual recipes. What you will learn Understand how to use machine learning algorithms for regression and classification problems;
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concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement;
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experts in the areas of artificial intelligence, the book covers the areas of AI for E-commerce and web applications, AI and sensors, augmented;
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for future AI solutions Acquire advanced AI, machine learning, and deep learning design skills Book DescriptionArtificial intelligence has;
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for updated research. This is especially relevant with frequent developments for the application of AI technology in many science and industry;
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TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks;
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developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e;
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lifelong learning in a strengthened model that can preserve the integrity of core values and the purpose of higher education. Impact of AI;
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cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the;
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cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the;
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industries through the use of AI. While highlighting topics such as pattern recognition, computational imaging, and machine learning, this;
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bored learning the theory underpinning AI. Instead, you will learn by experience and practice, and complete an engaging project in each chapter;
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NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement;
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Create AI applications in Python and lay the foundations for your career in data science Key Features Practical examples that explain key;
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, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI;
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AI is an integral part of every video game and this book helps game developers keep up with the constantly evolving technological advances;
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. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for;
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Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the;
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network Interactive AI for browser games using deep reinforcement learning Generative neural networks to generate music and pictures;
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applications Build and train deep learning models for implementing artificial intelligence Learn various algorithms to automate complex tasks Book;
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differences between supervised and unsupervised learning Discover the most recent advances and tools offered for AI development in the cloud Develop;
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