Scala for Data Science

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785289381
Total Pages : 416 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Scala for Data Science by : Pascal Bugnion

Download or read book Scala for Data Science written by Pascal Bugnion and published by Packt Publishing Ltd. This book was released on 2016-01-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Scala with different tools to build scalable, robust data science applications About This Book A complete guide for scalable data science solutions, from data ingestion to data visualization Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples provided Who This Book Is For If you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions. What You Will Learn Transform and filter tabular data to extract features for machine learning Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines Read, transform, and write data to both SQL and NoSQL databases in a functional manner Write robust routines to query web APIs Read data from web APIs such as the GitHub or Twitter API Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive In Detail Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines. This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala's emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks. This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions. Style and approach A tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

Hands-On Data Analysis with Scala

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789344263
Total Pages : 288 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Data Analysis with Scala by : Rajesh Gupta

Download or read book Hands-On Data Analysis with Scala written by Rajesh Gupta and published by Packt Publishing Ltd. This book was released on 2019-05-03 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data Key FeaturesA beginner's guide for performing data analysis loaded with numerous rich, practical examplesAccess to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysisDevelop applications in Scala for real-time analysis and machine learning in Apache SparkBook Description Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights What you will learnTechniques to determine the validity and confidence level of dataApply quartiles and n-tiles to datasets to see how data is distributed into many bucketsCreate data pipelines that combine multiple data lifecycle stepsUse built-in features to gain a deeper understanding of the dataApply Lasso regression analysis method to your dataCompare Apache Spark API with traditional Apache Spark data analysisWho this book is for If you are a data scientist or a data analyst who wants to learn how to perform data analysis using Scala, this book is for you. All you need is knowledge of the basic fundamentals of Scala programming.

Scala and Spark for Big Data Analytics

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Publisher : Packt Publishing Ltd
ISBN 13 : 1783550503
Total Pages : 786 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Scala and Spark for Big Data Analytics by : Md. Rezaul Karim

Download or read book Scala and Spark for Big Data Analytics written by Md. Rezaul Karim and published by Packt Publishing Ltd. This book was released on 2017-07-25 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Scala Programming for Big Data Analytics

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Author :
Publisher : Apress
ISBN 13 : 1484248104
Total Pages : 315 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Scala Programming for Big Data Analytics by : Irfan Elahi

Download or read book Scala Programming for Big Data Analytics written by Irfan Elahi and published by Apress. This book was released on 2019-07-05 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you’ll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks. The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala’s powerful collections system because many of Apache Spark’s APIs bear a strong resemblance to Scala collections. Along the way you’ll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You’ll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics. What You Will LearnSee the fundamentals of Scala as a general-purpose programming languageUnderstand functional programming and object-oriented programming constructs in ScalaUse Scala collections and functions Develop, package and run Apache Spark applications for big data analyticsWho This Book Is For Data scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics. /div

Frank Kane's Taming Big Data with Apache Spark and Python

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Publisher : Packt Publishing Ltd
ISBN 13 : 1787288307
Total Pages : 289 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Frank Kane's Taming Big Data with Apache Spark and Python by : Frank Kane

Download or read book Frank Kane's Taming Big Data with Apache Spark and Python written by Frank Kane and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.

Scala for Machine Learning

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Publisher : Packt Publishing Ltd
ISBN 13 : 178712620X
Total Pages : 740 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Scala for Machine Learning by : Patrick R. Nicolas

Download or read book Scala for Machine Learning written by Patrick R. Nicolas and published by Packt Publishing Ltd. This book was released on 2017-09-26 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Scala and Machine Learning to study and construct systems that can learn from data About This Book Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala Take your expertise in Scala programming to the next level by creating and customizing AI applications Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you're a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. 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! 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 Dive into neural networks and some deep learning architecture Apply some basic multiarm-bandit algorithms 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 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 design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you 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. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naive Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You'll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.

Scala: Guide for Data Science Professionals

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Publisher : Packt Publishing Ltd
ISBN 13 : 1787281035
Total Pages : 1101 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Scala: Guide for Data Science Professionals by : Pascal Bugnion

Download or read book Scala: Guide for Data Science Professionals written by Pascal Bugnion and published by Packt Publishing Ltd. This book was released on 2017-02-24 with total page 1101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scala will be a valuable tool to have on hand during your data science journey for everything from data cleaning to cutting-edge machine learning About This Book Build data science and data engineering solutions with ease An in-depth look at each stage of the data analysis process — from reading and collecting data to distributed analytics Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulations, and source code Who This Book Is For This learning path is perfect for those who are comfortable with Scala programming and now want to enter the field of data science. Some knowledge of statistics is expected. What You Will Learn Transfer and filter tabular data to extract features for machine learning Read, clean, transform, and write data to both SQL and NoSQL databases Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Load data from HDFS and HIVE with ease Run streaming and graph analytics in Spark for exploratory analysis Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Master probabilistic models for sequential data In Detail Scala is especially good for analyzing large sets of data as the scale of the task doesn't have any significant impact on performance. Scala's powerful functional libraries can interact with databases and build scalable frameworks — resulting in the creation of robust data pipelines. The first module introduces you to Scala libraries to ingest, store, manipulate, process, and visualize data. Using real world examples, you will learn how to design scalable architecture to process and model data — starting from simple concurrency constructs and progressing to actor systems and Apache Spark. After this, you will also learn how to build interactive visualizations with web frameworks. Once you have become familiar with all the tasks involved in data science, you will explore data analytics with Scala in the second module. You'll see how Scala can be used to make sense of data through easy to follow recipes. You will learn about Bokeh bindings for exploratory data analysis and quintessential machine learning with algorithms with Spark ML library. You'll get a sufficient understanding of Spark streaming, machine learning for streaming data, and Spark graphX. Armed with a firm understanding of data analysis, you will be ready to explore the most cutting-edge aspect of data science — machine learning. The final module teaches you the A to Z of machine learning with Scala. You'll explore Scala for dependency injections and implicits, which are used to write machine learning algorithms. You'll also explore machine learning topics such as clustering, dimentionality reduction, Naive Bayes, Regression models, SVMs, neural networks, and more. This learning path combines some of the best that Packt has to offer into one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala Data Analysis Cookbook, Arun Manivannan Scala for Machine Learning, Patrick R. Nicolas Style and approach A complete package with all the information necessary to start building useful data engineering and data science solutions straight away. It contains a diverse set of recipes that cover the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala.

Learning Scala

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449368840
Total Pages : 255 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Learning Scala by : Jason Swartz

Download or read book Learning Scala written by Jason Swartz and published by "O'Reilly Media, Inc.". This book was released on 2014-12-11 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why learn Scala? You don’t need to be a data scientist or distributed computing expert to appreciate this object-oriented functional programming language. This practical book provides a comprehensive yet approachable introduction to the language, complete with syntax diagrams, examples, and exercises. You’ll start with Scala's core types and syntax before diving into higher-order functions and immutable data structures. Author Jason Swartz demonstrates why Scala’s concise and expressive syntax make it an ideal language for Ruby or Python developers who want to improve their craft, while its type safety and performance ensures that it’s stable and fast enough for any application. Learn about the core data types, literals, values, and variables Discover how to think and write in expressions, the foundation for Scala's syntax Write higher-order functions that accept or return other functions Become familiar with immutable data structures and easily transform them with type-safe and declarative operations Create custom infix operators to simplify existing operations or even to start your own domain-specific language Build classes that compose one or more traits for full reusability, or create new functionality by mixing them in at instantiation

Scala Machine Learning Projects

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Publisher : Packt Publishing Ltd
ISBN 13 : 1788471474
Total Pages : 461 pages
Book Rating : 4.7/5 (884 download)

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Book Synopsis Scala Machine Learning Projects by : Md. Rezaul Karim

Download or read book Scala Machine Learning Projects written by Md. Rezaul Karim and published by Packt Publishing Ltd. This book was released on 2018-01-31 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. Key Features Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Book Description Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. What you will learn Apply advanced regression techniques to boost the performance of predictive models Use different classification algorithms for business analytics Generate trading strategies for Bitcoin and stock trading using ensemble techniques Train Deep Neural Networks (DNN) using H2O and Spark ML Utilize NLP to build scalable machine learning models Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application Learn how to use autoencoders to develop a fraud detection application Implement LSTM and CNN models using DeepLearning4j and MXNet Who this book is for If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful.

Machine Learning with Scala Quick Start Guide

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Publisher :
ISBN 13 : 9781789345070
Total Pages : 220 pages
Book Rating : 4.3/5 (45 download)

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Book Synopsis Machine Learning with Scala Quick Start Guide by : Rezaul Karim

Download or read book Machine Learning with Scala Quick Start Guide written by Rezaul Karim and published by . This book was released on 2019-04-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 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. 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, Naïve 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.

Hands-on Scala Programming: Learn Scala in a Practical, Project-Based Way

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Publisher :
ISBN 13 : 9789811456930
Total Pages : 414 pages
Book Rating : 4.4/5 (569 download)

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Book Synopsis Hands-on Scala Programming: Learn Scala in a Practical, Project-Based Way by : Haoyi Li

Download or read book Hands-on Scala Programming: Learn Scala in a Practical, Project-Based Way written by Haoyi Li and published by . This book was released on 2020-07-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Scala teaches you how to use the Scala programming language in a practical, project-based fashion. This book is designed to quickly teach an existing programmer everything needed to go from "hello world" to building production applications like interactive websites, parallel web crawlers, and distributed systems in Scala. In the process you will learn how to use the Scala language to solve challenging problems in an elegant and intuitive manner.

Advanced Analytics with Spark

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912731
Total Pages : 276 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Advanced Analytics with Spark by : Sandy Ryza

Download or read book Advanced Analytics with Spark written by Sandy Ryza and published by "O'Reilly Media, Inc.". This book was released on 2015-04-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find these patterns useful for working on your own data applications. Patterns include: Recommending music and the Audioscrobbler data set Predicting forest cover with decision trees Anomaly detection in network traffic with K-means clustering Understanding Wikipedia with Latent Semantic Analysis Analyzing co-occurrence networks with GraphX Geospatial and temporal data analysis on the New York City Taxi Trips data Estimating financial risk through Monte Carlo simulation Analyzing genomics data and the BDG project Analyzing neuroimaging data with PySpark and Thunder

Scala:Applied Machine Learning

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Publisher : Packt Publishing Ltd
ISBN 13 : 178712455X
Total Pages : 1265 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Scala:Applied Machine Learning by : Pascal Bugnion

Download or read book Scala:Applied Machine Learning written by Pascal Bugnion and published by Packt Publishing Ltd. This book was released on 2017-02-23 with total page 1265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features About This Book Build functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples provided Leverage your expertise in Scala programming to create and customize your own scalable machine learning algorithms Experiment with different techniques; evaluate their benefits and limitations using real-world financial applications Get to know the best practices to incorporate new Big Data machine learning in your data-driven enterprise and gain future scalability and maintainability Who This Book Is For This Learning Path is for engineers and scientists who are familiar with Scala and want to learn how to create, validate, and apply machine learning algorithms. It will also benefit software developers with a background in Scala programming who want to apply machine learning. What You Will Learn Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to perform technical analysis of financial markets Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions. The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial. The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala for Machine Learning, Patrick Nicolas Mastering Scala Machine Learning, Alex Kozlov Style and approach A tutorial with complete examples, this course will give you the tools to start building useful data engineering and data science solutions straightaway. This course provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.

Functional Programming in Scala

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Author :
Publisher : Simon and Schuster
ISBN 13 : 1638353956
Total Pages : 457 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Functional Programming in Scala by : Paul Chiusano

Download or read book Functional Programming in Scala written by Paul Chiusano and published by Simon and Schuster. This book was released on 2014-09-01 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to the everyday business of coding. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, you'll find concrete examples and exercises that open up the world of functional programming. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Functional programming (FP) is a style of software development emphasizing functions that don't depend on program state. Functional code is easier to test and reuse, simpler to parallelize, and less prone to bugs than other code. Scala is an emerging JVM language that offers strong support for FP. Its familiar syntax and transparent interoperability with Java make Scala a great place to start learning FP. About the Book Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to their everyday work. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, you'll find concrete examples and exercises that open up the world of functional programming. This book assumes no prior experience with functional programming. Some prior exposure to Scala or Java is helpful. What's Inside Functional programming concepts The whys and hows of FP How to write multicore programs Exercises and checks for understanding About the Authors Paul Chiusano and Rúnar Bjarnason are recognized experts in functional programming with Scala and are core contributors to the Scalaz library. Table of Contents PART 1 INTRODUCTION TO FUNCTIONAL PROGRAMMING What is functional programming? Getting started with functional programming in Scala Functional data structures Handling errors without exceptions Strictness and laziness Purely functional state PART 2 FUNCTIONAL DESIGN AND COMBINATOR LIBRARIES Purely functional parallelism Property-based testing Parser combinators PART 3 COMMON STRUCTURES IN FUNCTIONAL DESIGN Monoids Monads Applicative and traversable functors PART 4 EFFECTS AND I/O External effects and I/O Local effects and mutable state Stream processing and incremental I/O

Mastering Java for Data Science

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1785887394
Total Pages : 355 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Mastering Java for Data Science by : Alexey Grigorev

Download or read book Mastering Java for Data Science written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. Style and approach This is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.

Programming Scala

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491950153
Total Pages : 742 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Programming Scala by : Dean Wampler

Download or read book Programming Scala written by Dean Wampler and published by "O'Reilly Media, Inc.". This book was released on 2014-12-04 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up to speed on Scala, the JVM language that offers all the benefits of a modern object model, functional programming, and an advanced type system. Packed with code examples, this comprehensive book shows you how to be productive with the language and ecosystem right away, and explains why Scala is ideal for today's highly scalable, data-centric applications that support concurrency and distribution. This second edition covers recent language features, with new chapters on pattern matching, comprehensions, and advanced functional programming. You’ll also learn about Scala’s command-line tools, third-party tools, libraries, and language-aware plugins for editors and IDEs. This book is ideal for beginning and advanced Scala developers alike. Program faster with Scala’s succinct and flexible syntax Dive into basic and advanced functional programming (FP) techniques Build killer big-data apps, using Scala’s functional combinators Use traits for mixin composition and pattern matching for data extraction Learn the sophisticated type system that combines FP and object-oriented programming concepts Explore Scala-specific concurrency tools, including Akka Understand how to develop rich domain-specific languages Learn good design techniques for building scalable and robust Scala applications

Programming in Scala

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Author :
Publisher : Artima Inc
ISBN 13 : 0981531601
Total Pages : 778 pages
Book Rating : 4.9/5 (815 download)

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Book Synopsis Programming in Scala by : Martin Odersky

Download or read book Programming in Scala written by Martin Odersky and published by Artima Inc. This book was released on 2008 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive step-by-step guide