Machine learning.
Overview
Works: | 36 works in 36 publications in 36 languages |
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Titles
Information theoretic learning : Renyi's entropy and kernel perspectives
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Data-based methods for materials design and discovery : basic ideas and general methods
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Machine learning for business : using Amazon SageMaker and Jupyter
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Applied supervised learning with R : use machine learning libraries of R to build models that solve business problems and predict future trends
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Artificial Intelligence with Python Cookbook : proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6
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Deep learning for beginners : a beginner's guide to getting up and running with deep learning from scratch using python
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TensorFlow 2.0 computer vision cookbook : implement machine learning solutions to overcome various computer vision challenges
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Practical machine learning for computer vision : end-to-end machine learning for images
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Interpretable machine learning with Python : learn to build interpretable high-performance models with hands-on real-world examples
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Deep learning with Python : learn best practices of deep learning models with PyTorch
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Guide to deep learning basics : logical, historical and philosophical perspectives
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Programming with TensorFlow : solution for edge computing applications
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Natural language processing with PyTorch : build intelligent language applications using deep learning
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Generative deep learning : teaching machines to paint, write, compose, and play
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