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Industrial Machine Learning

80,24 €*

Sofort verfügbar, Lieferzeit: 1-3 Tage

Produktnummer: 1828e2c418489f4839a812969980501334
Autor: Vermeulen, Andreas François
Themengebiete: AI Artificial Intelligence Big data Data lake Data science Evolutionary computing Machine learning Reinforcement learning Supervised learning Unsupervised learning
Veröffentlichungsdatum: 01.12.2019
EAN: 9781484253151
Sprache: Englisch
Seitenzahl: 637
Produktart: Kartoniert / Broschiert
Verlag: APRESS
Untertitel: Using Artificial Intelligence as a Transformational Disruptor
Produktinformationen "Industrial Machine Learning"
Understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI). You will learn to apply ML to data lakes in various industries, supplying data professionals with the advanced skills required to handle the future of data engineering and data science. Data lakes currently generated by worldwide industrialized business activities are projected to reach 35 zettabytes (ZB) as the Fourth Industrial Revolution produces an exponential increase of volume, velocity, variety, variability, veracity, visualization, and value. Industrialization of ML evolves from AI and studying pattern recognition against the increasingly unstructured resource stored in data lakes.Industrial Machine Learning supplies advanced, yet practical examples in different industries, including finance, public safety, health care, transportation, manufactory,supply chain, 3D printing, education, research, and data science. The book covers: supervised learning, unsupervised learning, reinforcement learning, evolutionary computing principles, soft robotics disruptors, and hard robotics disruptors.What You Will LearnGenerate and identify transformational disruptors of artificial intelligence (AI)Understand the field of machine learning (ML) and apply it to handle big data and process the data lakes in your environmentHone the skills required to handle the future of data engineering and data scienceWho This Book Is ForIntermediate to expert level professionals in the fields of data science, data engineering, machine learning, and data management

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