#
Machine learning
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The concept ** Machine learning** represents the subject, aboutness, idea or notion of resources found in **European University Institute**.

The Resource
Machine learning
Resource Information

The concept

**Machine learning**represents the subject, aboutness, idea or notion of resources found in**European University Institute**.- Label
- Machine learning

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- AI and machine learning
- AI and machine learning for coders : a programmer's guide to artificial intelligence
- Advanced data analytics using Python : with machine learning, deep learning and NLP examples
- Advanced forecasting with Python : with state-of-the-art-models including LSTMs, Facebook's Prophet, and Amazon's DeepAR
- Advanced structured prediction
- Advances in financial machine learning
- Algorithmic Governance and Governance of Algorithms : Legal and Ethical Challenges
- An introduction to machine learning & deep neutral networks
- An introduction to machine learning in quantitative finance
- Applied deep learning : a case-based approach to understanding deep neural networks
- Applied text analysis with Python : enabling language-aware data products with machine learning
- Artificial Intelligence Applications for Smart Societies : Recent Advances
- Artificial intelligence : a guide for thinking humans
- Artificial intelligence basics : a non-technical introduction
- Artificial intelligence for business optimization : research and applications
- Artificial intelligence, machine learning, and deep learning
- Bayesian Optimization and Data Science
- Bayesian Optimization with Application to Computer Experiments
- Bayesian artificial intelligence
- Bayesian reasoning and machine learning
- Big data and machine learning in quantitative investment
- Big data, IoT, and machine learning : tools and applications
- Black Box Optimization, Machine Learning, and No-Free Lunch Theorems
- Business data science : combining machine learning and economics to optimize, automate, and accelerate business decisions
- Business forecasting : the emerging role of artificial intelligence and machine learning
- Compressed Sensing and Its Applications : Third International MATHEON Conference 2017
- Computational Reconstruction of Missing Data in Biological Research
- Cybersecurity in Digital Transformation : Scope and Applications
- Data driven approaches for health care : machine learning for identifying high utilizers
- Data science
- Data science revealed : with feature engineering, data visualization, pipeline development, and hyperparameter tuning
- Data science with Python and Dask
- Database Systems for Advanced Applications : 25th International Conference, DASFAA 2020, Jeju, South Korea, September 24â€“27, 2020, Proceedings, Part I
- Deep Learning Architectures : A Mathematical Approach
- Deep Reinforcement Learning : Fundamentals, Research and Applications
- Deep learning
- Deep learning
- Deep learning : a practitioner's approach
- Deep learning and linguistic representation
- Deep learning for data analytics : foundations, biomedical applications, and challenges
- Deep learning from scratch : building with Python from first principles
- Deep learning systems : algorithms, compilers, and processors for large-scale production
- Deep learning techniques for biomedical and health informatics
- Deep learning with Python
- Deep learning with Python : learn best practices of deep learning models with PyTorch
- Domain Adaptation in Computer Vision with Deep Learning
- Elements of causal inference : foundations and learning algorithms
- Embracing Industry 4.0 : Selected Articles from MUCET 2019
- First-order and Stochastic Optimization Methods for Machine Learning
- Foundations of machine learning
- Fundamentals of machine learning for predictive data analytics : algorithms, worked examples, and case studies
- Fundamentals of machine learning for predictive data analytics : algorithms, worked examples, and case studies
- GIS and Machine Learning for Small Area Classifications in Developing Countries
- Generative Adversarial Networks for Image Generation
- Genetic algorithms in search, optimization, and machine learning
- Graph algorithms : practical examples in Apache Spark and Neo4j
- Handbook of Big Geospatial Data
- Hands-on Scikit-Learn for machine learning applications : data science fundamentals with Python
- Hands-on machine learning with R
- Hands-on unsupervised learning using Python : how to build applied machine learning solutions from unlabeled data
- Harvard data science review : HDSR : a microscopic, telescopic, and kaleidoscopic view of data science
- Identity, Institutions and Governance in an AI World : Transhuman Relations
- Implementing machine learning for finance : a systematic approach to predictive risk and performance analysis for investment portfolios
- Induction : processes of inference, learning, and discovery
- Innovative Learning Environments in STEM Higher Education : Opportunities, Challenges, and Looking Forward
- Introducing machine learning
- Introduction to deep learning
- Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R
- Introduction to machine learning
- Introduction to machine learning
- Introduction to machine learning with R : rigorous mathematical analysis
- Just Enough R! : An Interactive Approach to Machine Learning and Analytics
- Large-scale kernel machines
- Learn R for applied statistics : with data visualizations, regressions, and statistics
- Learn data mining through Excel : a step-by-step approach for understanding machine learning methods
- Learning from data : concepts, theory, and methods
- Learning to love data science : explorations of emerging technologies and platforms for predictive analytics, machine learning, digital manufacturing, and supply chain optimization
- Learning with kernels : support vector machines, regularization, optimization, and beyond
- MATLAB deep learning : with machine learning, neural networks and artificial intelligence
- MATLAB machine learning
- MATLAB machine learning recipes : a problem-solution approach
- Machine Learning Paradigms : Advances in Deep Learning-based Technological Applications
- Machine Learning for Authorship Attribution and Cyber Forensics
- Machine Learning in Elite Volleyball : Integrating Performance Analysis, Competition and Training Strategies
- Machine Learning in Python : essential techniques for predictive analysis
- Machine learning
- Machine learning : a concise introduction
- Machine learning : a probabilistic perspective
- Machine learning : hands-on for developers and technical professionals
- Machine learning and analytics in healthcare systems : principles and applications
- Machine learning and big data with KDB+/Q
- Machine learning and security : protecting systems with data and algorithms
- Machine learning applications using Python : cases studies from healthcare, retail, and finance
- Machine learning concepts with Python and the Jupyter Notebook environment : using Tensorflow 2.0
- Machine learning for asset managers
- Machine learning for big data analyis
- Machine learning for data streams : with practical examples in MOA
- Machine learning for healthcare : handling and managing data
- Machine learning for sustainable development
- Machine learning for time series forecasting with Python
- Machine learning pocket reference : working with structured data in Python
- Machine learning with Python cookbook : practical solutions from preprocessing to deep learning
- Machine learning with Spark and Python : essential techniques for predictive analytics
- Mathematics and programming for machine learning with R : from the ground up
- Meta-Analytics : consensus approaches and system patterns for data analysis
- Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
- Pattern recognition and machine learning
- Perturbations, optimization, and statistics
- Practical Java machine learning : projects with Google Cloud Platform and Amazon Web Services
- Practical MATLAB deep learning : a project-based approach
- Practical Machine Learning in R
- Practical data science with Python 3 : synthesizing actionable insights from data
- Practical machine learning for data analysis using Python
- Practical machine learning with Python : a problem-solver's guide to building real-world intelligent systems
- Practical time series analysis : prediction with statistics and machine learning
- Pragmatic AI : an introduction to cloud-based machine learning
- Predicting structured data
- Prediction, learning, and games
- Programming machine learning : from coding to deep learning
- Python 3 for Machine Learning
- Python for R users : a data science approach
- Python machine learning
- Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics
- Quantum machine learning : what quantum computing means to data mining
- Social media analytics for user behavior modeling : a task heterogeneity perspective
- Statistical Learning and Modeling in Data Analysis : Methods and Applications
- Statistical process monitoring using advanced data-driven and deep learning approaches : theory and practical applications
- Statistics and machine learning methods for EHR data : from data extraction to data analytics
- Step into the World of Mathematics : Math Is Beautiful and Belongs to All of Us
- Supervised learning with Python : concepts and practical implementation using Python
- The Calabi-Yau Landscape : From Geometry, to Physics, to Machine Learning
- Thinking machines : machine learning and its hardware implementation
- Thoughtful machine learning : [a test-driven approach]
- Understanding machine learning : from theory to algorithms
- Unsupervised machine learning for clustering in political and social research
- Views into the Chinese room : new essays on Searle and artificial intelligence

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`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.eui.eu/resource/suIc0NgHKcU/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.eui.eu/resource/suIc0NgHKcU/">Machine learning</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.eui.eu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.eui.eu/">European University Institute</a></span></span></span></span></div>`