Supervised and unsupervised machine learning made easy in Scala with this quick-start guide. Key Features Construct and deploy machine learning systems that learn from your data and give accurate predictions  Unleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala.  Solve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library  Book Description Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala.  The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naive Bayes algorithms.  It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala.  What you will learn Get acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j  Learn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data  Understand supervised and unsupervised learning techniques with best practices and pitfalls  Learn classification and regression analysis with linear regression, logistic regression, Naive Bayes, support vector machine, and tree-based ensemble techniques  Learn effective ways of clustering analysis with dimensionality reduction techniques  Learn recommender systems with collaborative filtering approach  Delve into deep learning and neural network architectures  Who this book is for This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. Some fundamental knowledge of Scala programming and some basics of statistics and linear algebra is all you need to get started with this book.Table of Contents Introduction to Machine Learning with Scala Scala for Regression Analysis Scala for Learning Classification Scala for Tree-based Ensemble Techniques Scala for Dimensonality Reduction and Clustering Scala for Recommender System Introduction to Deep Learning with Scala

Machine Learning with Scala Quick Start Guide: Leverage popular machine learning algorithms and techniques and implement them in Scala PDF

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