Scala For Machine Learning By Patrick R. Nicolas

Scala For Machine Learning By Patrick R. Nicolas
by Patrick R. Nicolas / / / PDF


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The book begins with an introduction 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. Next, you'll learn about data preprocessing and filtering techniques. Following this, you'll move on to clustering and dimension reduction, Naive Bayes, regression models, sequential data, regularization and kernelization, support vector machines, neural networks, generic algorithms, and re-enforcement learning. A review of the Akka framework and Apache Spark clusters concludes the tutorial.

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