Machine learning.
Overview
| Works: | 220 works in 148 publications in 148 languages | |
|---|---|---|
Titles
An inductive logic programming approach to statistical relational learning[electronic resource] /
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Approximation methods for efficient learning of Bayesian networks[electronic resource] /
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Detection and identification of rare audiovisual cues[electronic resource] /
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Ensemble machine learning[electronic resource] :methods and applications /
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The BOXES methodology[electronic resource] :black box dynamic control /
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Learning in non-stationary environments[electronic resource] :methods and applications /
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Intelligent data analysis for real-life applications[electronic resource] :theory and practice /
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Machine learning algorithms for problem solving in computational applications[electronic resource] :intelligent techniques /
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Machine learning in computer-aided diagnosis[electronic resource] :medical imaging intelligence and analysis /
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Machine learning approaches to bioinformatics[electronic resource] /
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Applied genetic programming and machine learning[electronic resource] /
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Machine interpretation of patterns[electronic resource] :image analysis and data mining /
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Pattern classification using ensemble methods[electronic resource] /
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Scientific data mining and knowledge discovery[electronic resource] :principles and foundations /
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Diagnostic test approaches to machine learning and commonsense reasoning systems[electronic resource] /
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Machine learning for human motion analysis[electronic resource] :theory and practice /
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Machine learning and knowledge discovery for engineering systems health management[electronic resource] /
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Data mining and machine learning in cybersecurity[electronic resource] /
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Machine learning in medicine - Cookbook two[electronic resource] /
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Robust recognition via information theoretic learning[electronic resource] /
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Computer vision and machine learning with RGB-D sensors[electronic resource] /
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Machine learning for adaptive many-core machines[electronic resource] :a practical approach /
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Shape understanding system[electronic resource] :machine understanding and human understanding /
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Grammar-based feature generation for time-series prediction[electronic resource] /
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Data mining with decision trees[electronic resource] :theory and applications /
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Multidimensional particle swarm optimization for machine learning and pattern recognition[electronic resource] /
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Kernel learning algorithms for face recognition[electronic resource] /
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Sample efficient multiagent learning in the presence of Markovian agents[electronic resource] /
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Hybrid classifiers[electronic resource] :methods of data, knowledge, and classifier combination /
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Analysis and design of machine learning techniques[electronic resource] :evolutionary solutions for regression, prediction, and control problems /
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Conformal prediction for reliable machine learning[electronic resource] :theory, adaptations, and applications /
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Quantum machine learning[electronic resource] :what quantum computing means to data mining /
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Reinforcement and systemic machine learning for decision making[electronic resource] /
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Autonomous learning systems[electronic resource] :from data streams to knowledge in real-time /
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Multi-agent machine learning[electronic resource] :a reinforcement approach /
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Learning with partially labeled and interdependent data[electronic resource] /
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Iterative learning control for electrical stimulation and stroke rehabilitation[electronic resource] /
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Machine learning paradigms[electronic resource] :applications in recommender systems /
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Machine learning in radiation oncology[electronic resource] :theory and applications /
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Machine learning for audio, image and video analysis[electronic resource] :theory and applications /
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Artificial intelligence applications in information and communication technologies[electronic resource] /
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Machine learning projects for .NET Developers[electronic resource] /
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Measures of complexity[electronic resource] :festschrift for Alexey Chervonenkis /
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Mathematical problems in data science[electronic resource] :theoretical and practical methods /
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Knowledge transfer between computer vision and text mining[electronic resource] :similarity-based learning approaches /
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From curve fitting to machine learning[electronic resource] :an illustrative guide to scientific data analysis and computational intelligence /
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Machine Learning Models and Algorithms for Big Data Classification[electronic resource] :Thinking with Examples for Effective Learning /
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Teaching learning based optimization algorithm[electronic resource] :and its engineering applications /
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Rule based systems for big data[electronic resource] :a machine learning approach /
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Learning from data streams in dynamic environments[electronic resource] /
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Big data analysis[electronic resource] :new algorithms for a new society /
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Machine learning techniques for gait biometric recognition[electronic resource] :using the ground reaction force /
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Advances in machine learning and data mining for astronomy[electronic resource] /
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Introduction to pattern recognition and machine learning[electronic resource] /
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Machine learning[electronic resource] :a Bayesian and optimization perspective /
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Machine learning for microbial phenotype prediction[electronic resource] /
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Instruction selection[electronic resource] :principles, methods, and applications /
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Machine learning in Python[electronic resource] :essential techniques for predictive analysis /
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Machine learning[electronic resource] :hands-on for developers and technical professionals /
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Data mining and machine learning in building energy analysis[electronic resource] /
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Fundamentals of machine learning for predictive data analytics :algorithms, worked examples, and case studies /
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Deep learning step by step with Python :a very gentle introduction to deep neural networks for practical data science /
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Getting started with TensorFlow :get up and running with the latest numerical computing library by Google and dive deeper into your data! /
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First contact with TensorFlow :get started with deep learning programming /
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Algorithmic advances in Riemannian geometry and applications[electronic resource] :for machine learning, computer vision, statistics, and optimization /
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Python machine learning :machine learning and deep learning with Python, scikit-learn, and TensorFlow /
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The deep learning A.I. playbook :strategy for disruptive artificial intelligence /
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Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /
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TensorFlow machine learning cookbook :explore machine learning concepts using the latest numerical computing library, TensorFlow, with the help of this comprehenisive cookbook /
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Introduction to deep learning using R :a step-by-step guide to learning and implementing deep learning models using R /
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Praxiseinstieg Deep Learning :mit Python, Caffe, TensorFlow und Spark eigene Deep-Learning-Anwendungen erstellen /
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Introduction to machine learning with applications in information security /
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Multiple instance learning[electronic resource] :foundations and algorithms /
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Machine learning for health informatics[electronic resource] :state-of-the-art and future challenges /
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Intelligent systems and applications[electronic resource] :proceedings of the International Computer Symposium (ICS) held at Taichung, Taiwan, December 12-14, 2014 /
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Advanced deep learning with Keras :apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more /
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PyTorch deep learning hands-on :apply modern AI techniques with CNNs, RNNs, GANs, reinforcement learning, and more /
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Deep learning illustrated :a visual, interactive guide to artificial intelligence /
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Deep learning with PyTorch :a practical approach to building neural network models using PyTorch /
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Machine learning for beginners 2019 :the ultimate guide to artificial intelligence, neural networks, and predictive modelling (data mining algorithms & applications for finance, business & marketing) /
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Hands-on machine learning for algorithmic trading :design and implement investment strategies based on smart algorithms that learn from data using Python /
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A machine learning, artificial intelligence approach to institutional effectiveness in higher education /
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Network anomaly detection[electronic resource] :a machine learning perspective /
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Feature engineering for machine learning and data analytics[electronic resource] /
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Machine learning refined[electronic resource] :foundations, algorithms, and applications /
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Understanding machine learning[electronic resource] :from theory to algorithms /
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Predicting hotspots[electronic resource] :using machine learning to understand civil conflict /
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Deep learning for autonomous vehicle control :algorithms, state-of-the-art, and future prospects /
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Fundamentals of deep learning :designing next-generation machine intelligence algorithms /
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TensorFlow for deep learning :from linear regression to reinforcement learning /
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Electrocardiogram signal classification and machine learning[electronic resource] :emerging research and opportunities /
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Enhancing software fault prediction with machine learning[electronic resource] :emerging research and opportunities /
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Deep learning for image processing applications[electronic resource] /
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Next-generation wireless networks meet advanced machine learning applications[electronic resource] /
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Machine learning techniques for improved business analytics[electronic resource] /
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Machine learning and cognitive science applications in cyber security[electronic resource] /
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Inference and learning systems for uncertain relational data[electronic resource] /
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Machine learning and deep learning in real-time applications[electronic resource] /
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Deep learning strategies for security enhancement in wireless sensor networks[electronic resource] /
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Smart agricultural services using deep learning, big data, and IoT[electronic resource] /
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Research advancements in smart technology, optimization, and renewable energy[electronic resource] /
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Challenges and applications for implementing machine learning in computer vision[electronic resource] /
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Advanced deep learning applications in big data analytics[electronic resource] /
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Machine learning and data analytics for predicting, managing, and monitoring disease[electronic resource] /
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Handbook of research on machine learning techniques for pattern recognition and information security[electronic resource] /
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Probabilistic foundations of statistical network analysis[electronic resource] /
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Blockchain, big data and machine learning[electronic resource] :trends and applications /
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Text mining with machine learning[electronic resource] :principles and techniques /
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Deep learning in computer vision[electronic resource] :principles and applications /
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Generalization with deep learning[electronic resource] :for improvement on sensing capability /
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Machine learning[electronic resource] :a journey to deep learning : with exercises and answers /
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Deep learning for EEG-based brain-computer interfaces[electronic resource] :representations, algorithms and applications /
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Intelligent security systems[electronic resource] :how artificial intelligence, machine learning and data science work for and against computer security /
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Images as data for social science research[electronic resource] :an introduction to convolutional neural nets for image classification /
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Demystifying big data, machine learning, and deep learning for healthcare analytics[electronic resource] /
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Machine learning and the internet of medical things in healthcare[electronic resource] /
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Big data analytics for intelligent healthcare management[electronic resource] /
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Human recognition in unconstrained environments[electronic resource] :using computer vision, pattern recognition and machine learning methods for biometrics /
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Deep learning for data analytics[electronic resource] :foundations, biomedical applications, and challenges /
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Machine learning applications for accounting disclosure and fraud detection[electronic resource] /
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Handbook of research on disease prediction through data analytics and machine learning[electronic resource] /
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Applications of advanced machine intelligence in computer vision and object recognition[electronic resource] :emerging research and opportunities /
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Handbook of research on machine and deep learning applications for cyber security[electronic resource] /
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Handbook of research on emerging trends and applications of machine learning[electronic resource] /
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Deep learning applications and intelligent decision making in engineering[electronic resource] /
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Machine learning applications in non-conventional machining processes[electronic resource] /
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Artificial Intelligence and machine learning applications in civil, mechanical, and industrial engineering[electronic resource] /
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Examining optoelectronics in machine vision and applications in industry 4.0[electronic resource] /
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Deep learning-based image analysis under constrained and unconstrained environments[electronic resource] /
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Probabilistic approaches for social media analysis[electronic resource] :data, community and influence /
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The lognormality principle and its applications in e-security, e-learning and e-health[electronic resource] /
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Recommender system with machine learning and artificial intelligence[electronic resource] :practical tools and applications in medical, agricultural and other industries /
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Introduction to deep learning for engineers[electronic resource] :using python and google cloud platform /
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Multi-armed bandits[electronic resource] :theory and applications to online learning in networks /
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Machine learning for solar array monitoring, optimization, and control[electronic resource] /
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Deep learning and parallel computing environment for bioengineering[electronic resource] /
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Machine learning in biotechnology and life sciences :build machine learning models using Python and deploy them on the cloud /
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AI applications for disease diagnosis and treatment[electronic resource] /
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Machine learning and AI techniques in interactive medical image analysis[electronic resource] /
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Applications of computational science in artificial intelligence[electronic resource] /
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Advances in deep learning applications for smart cities[electronic resource] /
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Applications of machine learning and deep learning for privacy and cybersecurity[electronic resource] /
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Controlling epidemics with mathematical and machine learning models[electronic resource] /
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Artificial intelligence and machine learning techniques for civil engineering[electronic resource] /
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Predictive analytics using statistics and big data[electronic resource] :concepts and modeling /
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Artificial intelligence and internet of things for renewable energy systems[electronic resource] /
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Robot learning human skills and intelligent control design[electronic resource] /
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Advanced AI techniques and applications in bioinformatics[electronic resource] /
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Machine learning for risk calculations[electronic resource] :a practitioner's view /
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Learning genetic algorithms with Python[electronic resource] :empower the performance of machine learning and AI models with the capabilities of a powerful search algorithm /
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A practical approach for machine learning and deep learning algorithms[electronic resource] :tools and techniques using MATLAB and Python /
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Hands-on supervised learning with Python[electronic resource] :learn how to solve machine learning problems with supervised learning algorithms using Python /
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Data science for business professionals[electronic resource] :a practical guide for beginners /
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Machine learning for beginners[electronic resource] :learn to build machine learning systems using Python /
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Machine learning cookbook with Python[electronic resource] :create ML and data analytics projects using some amazing open datasets /
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Practical data science with Jupyter[electronic resource] :explore data cleaning, pre-processing, data wrangling, feature engineering and machine learning using Python and Jupyter /
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Subjects