Leverage Scala and Machine Learning to construct and study systems that can learn from data
About This Book
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Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and source code
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Leverage your expertise in Scala programming to create and customize AI applications with your own scalable machine learning algorithms
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Experiment with different techniques, and evaluate their benefits and limitations using real-world financial applications, in a tutorial style
Who This Book Is For
Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!
In Detail
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 designs, biometrics, and trading strategies, to detection of genetic anomalies.
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.
