Machine Learning with Scala [Video]

Machine Learning with Scala [Video]

This video is included in a Mapt subscription
Alex Minnaar

1 customer reviews
Explore the most innovative and cutting edge machine learning techniques with Scala
$0.00
$30.00
$29.99p/m after trial
RRP $99.99
Subscription
Video
Start 30 Day Trial
Subscribe and access every Packt eBook & Video.
 
  • 5,000+ eBooks & Videos
  • 50+ New titles a month
  • 1 Free eBook/Video to keep every month
Start Free Trial
 
Preview in Mapt

Video Details

ISBN 139781785881350
Course Length1 hours and 58 minutes

Video Description

The ability to apply machine learning techniques to large datasets is becoming a highly sought-after skill in the world of technology. Scala can help you deliver key insights into your data—its unique capabilities as a language let you build sophisticated algorithms and statistical models. For this reason, machine learning and Scala fit together perfectly and knowledge of both would be beneficial for anyone entering the data science field.

The course starts with a general introduction to the Scala programming language. From there, you’ll be introduced to several practical machine learning algorithms from the areas of exploratory data analysis. You’ll look at supervised learning machine learning models for prediction and classification tasks, and unsupervised learning techniques such as clustering and dimensionality reduction and neural networks.

By the end, you will be comfortable applying machine learning algorithms to solve real-world problems using Scala.

Table of Contents

Introduction to Scala
The Course Overview
Functional Combinators in Scala
Scala Traits, Classes, and Objects
IntelliJ IDEA as an IDE
The Breeze Library for Linear Algebra
WISP for Plotting
Exploratory Data Analysis with Scala
Exploratory Data Analysis
Using DataFrames with Scala and Plotting with Breeze
Supervised Learning
Supervised Learning Problem Formulation
Two Basic Regression Algorithms
Implementing Linear Regression and GLMs in Scala
Two Basic Classification Algorithms
Implementing K-Nearest Neighbors and Naive Bayes in Scala
Model Selection
Unsupervised Learning
Unsupervised Learning Problem Formulation
Implementing K-means Algorithm in Scala
Mixture of Gaussians Clustering
Implementing Mixture of Gaussians Clustering in Scala
Dimensionality Reduction with Principle Component Analysis (PCA)
Implementing PCA in Scala
Neural Networks
Introduction to Feed-Forward Neural Networks
Implementing the Feed-Forward Neural Network in Scala
Introduction to Restricted Boltzmann Machines (RBMs)
Implementing Restricted Boltzmann Machines in Scala
Other Scala Frameworks for Machine Learning
The Akka Actor Model for Concurrency
A Multi-threaded K-Nearest Neighbors Implementation with Akka
Introduction to Apache Spark
Running Linear Regression on Spark with MLlib

What You Will Learn

  • Write Scala code implementing neural network models for prediction and clustering
  • Plot and analyze the structure of datasets with exploratory data analysis techniques using Scala
  • Use new and popular Scala frameworks such as Akka and Spark to implement machine learning algorithms and Scala libraries such as Breeze for numerical computing and plotting
  • Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, and neural networks
  • Use the power of MLlib libraries to implement machine learning with Spark
  • Work with the k-means algorithm and implement it in Scala with the real datasets
  • Get to know what dimensionality reduction is and explore the theory behind how the PCA algorithm works
  • Analyze and implement linear regression and GLMs in Scala and run them on real datasets
  • Use the Naive bayes algorithms and its methods to predict the probability of different classes based on various attributes

Authors

Table of Contents

Introduction to Scala
The Course Overview
Functional Combinators in Scala
Scala Traits, Classes, and Objects
IntelliJ IDEA as an IDE
The Breeze Library for Linear Algebra
WISP for Plotting
Exploratory Data Analysis with Scala
Exploratory Data Analysis
Using DataFrames with Scala and Plotting with Breeze
Supervised Learning
Supervised Learning Problem Formulation
Two Basic Regression Algorithms
Implementing Linear Regression and GLMs in Scala
Two Basic Classification Algorithms
Implementing K-Nearest Neighbors and Naive Bayes in Scala
Model Selection
Unsupervised Learning
Unsupervised Learning Problem Formulation
Implementing K-means Algorithm in Scala
Mixture of Gaussians Clustering
Implementing Mixture of Gaussians Clustering in Scala
Dimensionality Reduction with Principle Component Analysis (PCA)
Implementing PCA in Scala
Neural Networks
Introduction to Feed-Forward Neural Networks
Implementing the Feed-Forward Neural Network in Scala
Introduction to Restricted Boltzmann Machines (RBMs)
Implementing Restricted Boltzmann Machines in Scala
Other Scala Frameworks for Machine Learning
The Akka Actor Model for Concurrency
A Multi-threaded K-Nearest Neighbors Implementation with Akka
Introduction to Apache Spark
Running Linear Regression on Spark with MLlib

Video Details

ISBN 139781785881350
Course Length1 hours and 58 minutes
Read More
From 1 reviews

Read More Reviews

Recommended for You

Advanced Functional Data Structures and Algorithms [Video] Book Cover
Advanced Functional Data Structures and Algorithms [Video]
$ 124.99
$ 37.50
Finishing Touches on the Game [Video] Book Cover
Finishing Touches on the Game [Video]
$ 124.99
$ 37.50
Build scalable applications with Apache Kafka [Video] Book Cover
Build scalable applications with Apache Kafka [Video]
$ 124.99
$ 37.50
Building Data Streaming Applications with Apache Kafka Book Cover
Building Data Streaming Applications with Apache Kafka
$ 35.99
$ 18.00