John D. Kelleher - Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies epub indir internet üzerinden

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Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies adlı kitabı telefonunuzda, bilgisayarınızda veya tabletinizde EPUB biçiminde okumak için "okuyucu" uygulamasını ücretsiz veya satın almanız gerekir - siz karar verin. İşlevsel olarak özgür "okuyucular" nadiren ücretli olanlara yol verir ve bazen onları aşar. Bazen daha yavaş çalışır veya reklam içerir. Ücretli uygulamalar daha güzel görünür, daha az yavaşlar, aynı işlevsellik ile telefonun belleğinde genellikle daha az yer kaplarlar. Veya John D. Kelleher adresinden çevrimiçi olarak Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies kitap okumak için bir site bulabilirsiniz. EPUB, kayan bir düzene sahip bir biçimdir, yani kitabın metni, örneğin Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, akıllı telefonunuzun veya tabletinizin ekran boyutuna otomatik olarak ayarlanır - manuel olarak ölçeklendirmeniz gerekmez. Son aşamada, biçim bilgisayarlar, akıllı telefonlar ve tabletler tarafından desteklenen 5.2 sürümüne güncellenir. Gutenberg Serbest Kütüphanesi, 2008 yılında Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies gibi kitapları ve diğer basılı yayınları ve kitapları dijitalleştirmek ve saklamak için bu biçimi seçti. Yavaş yavaş, 2010'a kadar, daha önce kendi LRF uzantısını (BBeB) kullanan Sony, belgeleri bu biçime dönüştürdü. E-kitapların ve "okuyucuların" artan popülaritesi ile birlikte popülerlik kazanıyor. İlk kez 1999'da ABD'de ortaya çıktı, farklı olarak adlandırıldı - Açık eKitap Yayını (OEB). Geliştirici - Uluslararası Dijital Yayıncılık Forumu, IDPF kısaltması: Uluslararası Dijital Yayıncılık Forumu. 2007 yılında, “forum”, doğrudan “Elektronik Yayıncılık” olan ve tam anlamıyla “Elektronik Yayıncılık” olarak kısaltılan geliştirmenin son versiyonunu tanıttı.

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Yazar Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies John D. Kelleher Brian Mac Namee Aoife D'Arcy

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.The book is accessible, offering nontechnical explanations of the ideas underpinning each approach before introducing mathematical models and algorithms. It is focused and deep, providing students with detailed knowledge on core concepts, giving them a solid basis for exploring the field on their own. Both early chapters and later case studies illustrate how the process of learning predictive models fits into the broader business context. The two case studies describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book can be used as a textbook at the introductory level or as a reference for professionals.

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