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    Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition Patrick R. Nicolas

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition Patrick R. Nicolas - okladka książki

    Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition Patrick R. Nicolas - okladka książki

    Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition Patrick R. Nicolas - audiobook MP3

    Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition Patrick R. Nicolas - audiobook CD

    Autor:
    Patrick R. Nicolas
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    740
    Dostępne formaty:
         PDF
         ePub
         Mobi
    The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies.

    The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naïve Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You’ll move on to evolutionary computing, multibandit algorithms, and reinforcement learning.

    Finally, the book includes a comprehensive overview of parallel computing in Scala and
    Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala.

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    O autorze książki

    Patrick R. Nicolas is the director of engineering at Agile SDE, California. He has more than 25 years of experience in software engineering and building applications in C++, Java, and more recently in Scala/Spark, and has held several managerial positions. His interests include real-time analytics, modeling, and the development of nonlinear models.

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