367 hasil untuk machine learning
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Buku Teks lengkap
Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2015), Porto, Portugal
International audience
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Buku Teks lengkap
Proceedings of the 4nd Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2017), Skopje, Macédoine
International audience
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Buku Teks lengkap
Jiànzhú néng hào fēnxī zhōng de shùjù wājué yǔ jīqì xuéxí (Data Mining and Machine Learning in Building Energy Analysis)
建筑的能源性能受很多因素的影响，《建筑能耗分析中的数据挖掘与机器学习》针对建筑的复杂特性，重点研究用新的数据挖掘和机器学习方法来对建筑能耗进行准确的预测、分析或者故障检测/诊断。《建筑能耗分析中的数据挖掘与机器学习》涉及建筑能耗分析的建模及用于模型降阶与并行计算的技术和相关算法，同时提出了新的算法用于能耗分析预测及建筑能耗故障检测/诊断，既有一定的理论深度，又有较好的应用宽度。我国建筑能耗占社会总能耗很大的比例，目前对建筑能耗分析的理论、技术和方法所做的研究工作与国际先进水平有相当大的差距，在实际建筑中实施建筑能耗管理与分析的水平也较低。因此，当前特别迫切需要学习并借鉴国外在建筑能耗管理、优化…
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Buku Teks lengkap
Machine Learning for Networking: Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3–5, 2019, Revised Selected Papers
International audience
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Buku Teks lengkap
Artificial Intelligence in Precision Medicine: Integrating Machine Learning, Deep Neural Networks, and Data Analytics for Diagnostic Imaging, Surgical Interventions, and Specialized Therapeutic Applications
ChaptersChapter 1: Artificial Intelligence Algorithms for Enhanced Computed Tomography Scan Interpretation: Deep Learning Models for Automated Lesion Detection, Image Reconstruction, and Quantitative Analysis in Clinical Radiology (Negin Mehdinejad)Chapter 2: Machine Learning Integration in…
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Buku Teks lengkap
Machine Learning and Knowledge Extraction: First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings
Book Front Matter of LNCS 10410
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Buku Teks lengkap
Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25–28, 2020, Proceedings
Book Front Matter of LNCS 12279
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Buku Teks lengkap
Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings
Book Front Matter of LNCS 11713
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Buku Teks lengkap
Machine Learning and Knowledge Extraction: 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021 Virtual Event, August 17–20, 2021, Proceedings
Book Front Matter of LNCS 12844
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Buku Teks lengkap
Machine Learning and Knowledge Extraction: Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Hamburg, Germany, August 27–30, 2018, Proceedings
Book Front Matter of LNCS 11015
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Buku Teks lengkap
with Lendasse, Amaury, Miche, Yoan, Maillet, Bertrand. 2013. Forecasting Financial Markets with Classified Tactical Signals., ESANN 2013: 21st European Symposium on Artificial Neural Networks, Computational Intelligence And Machine Learning Bruges April 24-25-26, 2013. : ESANN, 363-368 p.
International audience
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Buku Teks lengkap
Availability, Reliability, and Security in Information Systems: IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference, CD-ARES 2016, and Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016, Salzburg, Austria, August 31 - September 2, 2016, Proceedings
Book Front Matter of LNCS 9817
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Buku Teks lengkap
Metric Learning
…such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of…
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Buku Teks lengkap
Machine Translation
…the advent of computers, research has focused on the design of digital machine translation tools—computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in…
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Buku Teks lengkap
Physics-based Deep Learning
This digital book contains a practical and comprehensive introduction of everything related to deep learning in the context of physical simulations. As much as possible, all topics come with hands-on code examples in the form of Jupyter notebooks to quickly get started. Beyond standard supervised…