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Machine Learning with Scala Quick Start Guide

Machine Learning with Scala Quick Start Guide

By : Karim, Kumar N
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Machine Learning with Scala Quick Start Guide

Machine Learning with Scala Quick Start Guide

By: Karim, Kumar N

Overview of this book

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 Naïve 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.
Table of Contents (9 chapters)
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DL and ANNs

ANNs, which are inspired by how a human brain works, form the core of deep learning and its true realization. Today's revolution around deep learning would have not been possible without ANNs. Thus, to understand DL, we need to understand how neural networks work.

ANNs and the human brain

ANNs represent one aspect of the human nervous system and how the nervous system consists of a number of neurons that communicate with each other using axons. The receptors receive the stimuli either internally or from the external world. Then, they pass this information into the biological neurons for further processing.

There are a number of dendrites, in addition to another long extension called the axon. Toward its...

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