Machine Learning Support for Fault Diagnosis of System-on-Chip
Patrick Girard
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Developing Apps with GPT-4 and ChatGPT : Build Intelligent Chatbots, Content Generators, and More
Olivier Caelen
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Thinking Data Science : A Data Science Practitioner’s Guide
Poornachandra Sarang
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Data Mining for Co-location Patterns : Principles and Applications
Guoqing Zhou
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Linear Algebra for Data Science, Machine Learning, and Signal Processing
Jeffrey A. (University of Michigan, Ann Arbor) Fessler
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Tangles : A Structural Approach to Artificial Intelligence in the Empirical Sciences
Reinhard (Universitat Hamburg) Diestel
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Artificial Intelligence and Causal Inference
Momiao (University of Texas School of Public Health, USA) Xiong
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Deeper Learning : A Voice from Laboratory to Classroom
Hang Hu
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Justice Matters : Spiritual Care and Pastoral Theological Imaginations in Times of the COVID-19 Pandemic
Kyungsig Samuel (Claremont School of Theology, USA) Lee
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Deep Learning for Engineers
Tariq M. (Weber State University Ogden, UT) Arif
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Deep Learning for Time Series Cookbook : Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Vitor Cerqueira
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Emerging ICT Technologies and Cybersecurity : From AI and ML to Other Futuristic Technologies
Kutub Thakur
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Explainable and Interpretable Reinforcement Learning for Robotics
Aaron M. Roth
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Machine Learning for Environmental Noise Classification in Smart Cities
Ali Othman Albaji
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Kidney and Kidney Tumor Segmentation : MICCAI 2023 Challenge, KiTS 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings
Nicholas Heller
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MultiMedia Modeling : 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 – February 2, 2024, Proceedings, Part V
Stevan Rudinac
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Gaussian Processes for Machine Learning
Carl Edward (University of Cambridge) Rasmussen
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Deep Learning with Python
Francois Chollet
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Data-Driven Science and Engineering : Machine Learning, Dynamical Systems, and Control
Steven L. (University of Washington) Brunton
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Mathematics for Machine Learning
Marc Peter (University College London) Deisenroth
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