Free Download Mastering Machine Learning with R: Advanced machine learning techniques for building smart applications with R 3.5, 3rd Edition by Cory Lesmeister
English | January 31, 2019 | ISBN: 1789618002 | 354 pages | MOBI | 8.55 Mb
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Free Download Mastering Azure Machine Learning: Execute large-scale end-to-end machine learning with Azure, 2nd Edition
English | 2022 | ISBN: 9781803232416 | 624 Pages | True PDF EPUB | 28 MB
Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps.

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English | April 19, 2018 | ISBN: 9386551934 | 268 pages | MOBI | 14 Mb
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Free Download Machine Learning on Geographical Data Using Python: Introduction into Geodata with Applications and Use Cases by Joos Korstanje
English | July 21, 2022 | ISBN: 1484282868 | 327 pages | MOBI | 24 Mb
Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data in Python. This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data, and an overview of Python tools for geodata. Specifics and difficulties one may encounter when using geographical data are discussed: from coordinate systems and map projections to different geodata formats and types such as points, lines, polygons, and rasters. Analytics operations typically applied to geodata are explained such as clipping, intersecting, buffering, merging, dissolving, and erasing, with implementations in Python. Use cases and examples are included. The book also focuses on applying more advanced machine learning approaches to geographical data and presents interpolation, classification, regression, and clustering via examples and use cases. This book is your go-to resource for machine learning on geodata. It presents the basics of working with spatial data and advanced applications. Examples are presented using code (accessible at github.com/Apress/machine-learning-geographic-data-python) and facilitate learning by application.

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English | April 29, 2023 | ISBN: 9355518102 | 458 pages | MOBI | 103 Mb
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Free Download Machine Learning for Time Series: Use Python to forecast, predict, and detect anomalies with state-of-the-art machine learning methods, 2nd Edition by Ben Auffarth
English | March 11, 2024 | ISBN: 1837631336 | 392 pages | MOBI | 0.70 Mb
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Free Download Machine Learning for Sustainable Manufacturing in Industry 4.0: Concept, Concerns and Applications
English | 2024 | ISBN: 103239305X | 250 Pages | PDF (True) | 17 MB
The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

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English | 2023 | ISBN: 3031351134 | 314 Pages | PDF EPUB (True) | 88 MB
This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. In detail, it starts by describing the basics of machine learning and its potentials in Earth Sciences to solve geological problems. It describes the main Python tools devoted to ML, the typival workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work. The book provides many examples of ML application to Earth Sciences problems in many fields, such as the clustering and dimensionality reduction in petro-volcanological studies, the clustering of multi-spectral data, well-log data facies classification, and machine learning regression in petrology. Also, the book introduces the basics of parallel computing and how to scale ML models in the cloud. The book is devoted to Earth Scientists, at any level, from students to academics and professionals.

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English | July 29, 2022 | ISBN: 1800566018 | 396 pages | MOBI | 15 Mb
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English | 2023 | ISBN: 3031280156 | 1312 Pages | PDF EPUB (True) | 119 MB
This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.