Scala for Machine LearningPDF Download for free:
Book Description:
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.
What You Will Learn
- Build dynamic workflows for scientific computing
- Leverage open source libraries to extract patterns from time series
- Write your own classification, clustering, or evolutionary algorithm
- Perform relative performance tuning and evaluation of Spark
- Master probabilistic models for sequential data
- Experiment with advanced techniques such as regularization and kernelization
- Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters
- Apply key learning strategies to a technical analysis of financial markets
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