Scala Applied Machine Learning

Scala Applied Machine Learning PDF
Author: Pascal Bugnion
Publisher: Packt Publishing Ltd
ISBN: 178712455X
Size: 80.31 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 1265
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Scala Applied Machine Learning

by Pascal Bugnion, Scala Applied Machine Learning Books available in PDF, EPUB, Mobi Format. Download Scala Applied Machine Learning books, 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.


Machine Learning With Scala Quick Start Guide

Machine Learning with Scala Quick Start Guide PDF
Author: Md. Rezaul Karim
Publisher: Packt Publishing Ltd
ISBN: 1789345413
Size: 63.26 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 220
View: 3278

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Machine Learning With Scala Quick Start Guide

by Md. Rezaul Karim, Machine Learning With Scala Quick Start Guide Books available in PDF, EPUB, Mobi Format. Download Machine Learning With Scala Quick Start Guide books, 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.


Applied Machine Learning With Python

Applied Machine Learning with Python PDF
Author: Andrea Giussani
Publisher: EGEA spa
ISBN: 8823818869
Size: 29.95 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 168
View: 4655

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Applied Machine Learning With Python

by Andrea Giussani, Applied Machine Learning With Python Books available in PDF, EPUB, Mobi Format. Download Applied Machine Learning With Python books, This book gives the fundamental principles for developing Machine Learning applications with Python.


Applied Machine Learning With Python Second Edition

Applied Machine Learning with Python   Second edition PDF
Author: Andrea Giussani
Publisher: EGEA spa
ISBN: 8823881153
Size: 71.95 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 204
View: 7026

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Applied Machine Learning With Python Second Edition

by Andrea Giussani, Applied Machine Learning With Python Second Edition Books available in PDF, EPUB, Mobi Format. Download Applied Machine Learning With Python Second Edition books, This book gives the fundamental principles for developing Machine Learning applications with Python.


Mastering Scala Machine Learning

Mastering Scala Machine Learning PDF
Author: Alexander Kozlov
Publisher: Packt Publishing
ISBN: 9781785880889
Size: 40.79 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 310
View: 2182

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Mastering Scala Machine Learning

by Alexander Kozlov, Mastering Scala Machine Learning Books available in PDF, EPUB, Mobi Format. Download Mastering Scala Machine Learning books, Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and HadoopAbout This Book*This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data*Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning*Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainabilityWho This Book Is ForMastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required.What You Will Learn*Sharpen your functional programming skills in Scala using REPL*Apply standard and advanced machine learning techniques using Scala*Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data*Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data*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 ScalaIn DetailSince the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing.This book aims to take your knowledge to next level and help you impart that 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.Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala.


Programmieren Mit Scala

Programmieren mit Scala PDF
Author: Dean Wampler
Publisher: O'Reilly Germany
ISBN: 3897216485
Size: 36.14 MB
Format: PDF, Mobi
Category : Computers
Languages : de
Pages : 480
View: 565

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Programmieren Mit Scala

by Dean Wampler, Programmieren Mit Scala Books available in PDF, EPUB, Mobi Format. Download Programmieren Mit Scala books, Sie ist elegant, schlank, modern und flexibel: Die Rede ist von Scala, der neuen Programmiersprache für die Java Virtual Machine (JVM). Sie vereint die Vorzüge funktionaler und objektorientierter Programmierung, ist typsicherer als Java, lässt sich nahtlos in die Java-Welt integrieren – und eine in Scala entwickelte Anwendung benötigt oft nur einen Bruchteil der Codezeilen ihres Java-Pendants. Kein Wunder, dass immer mehr Firmen, deren große, geschäftskritische Anwendungen auf Java basieren, auf Scala umsteigen, um ihre Produktivität und die Skalierbarkeit ihrer Software zu erhöhen. Das wollen Sie auch? Dann lassen Sie sich von den Scala-Profis Dean Wampler und Alex Payne zeigen, wie es geht. Ihre Werkzeugkiste: Schon bevor Sie loslegen, sind Sie weiter, als Sie denken: Sie können Ihre Java-Programme weiter verwenden, Java-Bibliotheken nutzen, Java von Scala aus aufrufen und Scala von Java aus. Auch Ihre bevorzugten Entwicklungswerkzeuge wie NetBeans, IntelliJ IDEA oder Eclipse stehen Ihnen weiter zur Verfügung, dazu Kommandozeilen-Tools, Plugins für Editoren, Werkzeuge von Drittanbietern – und natürlich Ihre Programmiererfahrung. In Programmieren mit Scala erfahren Sie, wie Sie sich all das zunutze machen. Das Hybridmodell: Die Paradigmen "funktional" und "objektorientiert" sind keine Gegensätze, sondern ergänzen sich unter dem Scala-Dach zu einem sehr produktiven Ganzen. Nutzen Sie die Vorteile funktionaler Programmierung, wann immer sich das anbietet – und seien Sie so frei, auf die guten alten Seiteneffekte zu bauen, wenn Sie das für nötig halten. Futter für die Profis: Skalierbare Nebenläufigkeit mit Aktoren, Aufzucht und Pflege von XML mit Scala, Domainspezifische Sprachen, Tipps zum richtigen Anwendungsdesign – das sind nur ein paar der fortgeschrittenen Themen, in die Sie mit den beiden Autoren eintauchen. Danach sind Sie auch Profi im Programmieren mit Scala.


Sieben Wochen Sieben Sprachen Prags

Sieben Wochen  sieben Sprachen  Prags  PDF
Author: Bruce A. Tate
Publisher: O'Reilly Germany
ISBN: 3897213230
Size: 54.95 MB
Format: PDF, Kindle
Category : Computers
Languages : de
Pages : 360
View: 6623

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Sieben Wochen Sieben Sprachen Prags

by Bruce A. Tate, Sieben Wochen Sieben Sprachen Prags Books available in PDF, EPUB, Mobi Format. Download Sieben Wochen Sieben Sprachen Prags books, Mit diesen sieben Sprachen erkunden Sie die wichtigsten Programmiermodelle unserer Zeit. Lernen Sie die dynamische Typisierung kennen, die Ruby, Python und Perl so flexibel und verlockend macht. Lernen Sie das Prototyp-System verstehen, das das Herzstück von JavaScript bildet. Erfahren Sie, wie das Pattern Matching in Prolog die Entwicklung von Scala und Erlang beeinflusst hat. Entdecken Sie, wie sich die rein funktionale Programmierung in Haskell von der Lisp-Sprachfamilie, inklusive Clojure, unterscheidet. Erkunden Sie die parallelen Techniken, die das Rückgrat der nächsten Generation von Internet-Anwendungen bilden werden. Finden Sie heraus, wie man Erlangs "Lass es abstürzen"-Philosophie zum Aufbau fehlertoleranter Systeme nutzt. Lernen Sie das Aktor-Modell kennen, das das parallele Design bei Io und Scala bestimmt. Entdecken Sie, wie Clojure die Versionierung nutzt, um einige der schwierigsten Probleme der Nebenläufigkeit zu lösen. Hier finden Sie alles in einem Buch. Nutzen Sie die Konzepte einer Sprache, um kreative Lösungen in einer anderen Programmiersprache zu finden – oder entdecken Sie einfach eine Sprache, die Sie bisher nicht kannten. Man kann nie wissen – vielleicht wird sie sogar eines ihrer neuen Lieblingswerkzeuge.


Machine Learning With Spark Second Edition

Machine Learning with Spark   Second Edition PDF
Author: Rajdeep Dua
Publisher:
ISBN: 9781785889936
Size: 77.28 MB
Format: PDF
Category :
Languages : en
Pages : 572
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Machine Learning With Spark Second Edition

by Rajdeep Dua, Machine Learning With Spark Second Edition Books available in PDF, EPUB, Mobi Format. Download Machine Learning With Spark Second Edition books, Develop intelligent machine learning systems with SparkAbout This Book*Get to the grips with the latest version of Apache Spark*Utilize Spark's machine learning library to implement predictive analytics*Leverage Spark's powerful tools to load, analyze, clean, and transform your dataWho This Book Is ForIf you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages.What You Will Learn*Get hands-on with the latest version of Spark ML*Create your first Spark program with Scala and Python*Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2*Access public machine learning datasets and use Spark to load, process, clean, and transform data*Use Spark's machine learning library to implement programs by utilizing well-known machine learning models*Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models*Write Spark functions to evaluate the performance of your machine learning modelsIn DetailSpark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression.This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.


Machine Learning

Machine Learning PDF
Author: Thomas Farth
Publisher: Createspace Independent Publishing Platform
ISBN: 9781729563953
Size: 52.41 MB
Format: PDF, Docs
Category :
Languages : en
Pages : 84
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Machine Learning

by Thomas Farth, Machine Learning Books available in PDF, EPUB, Mobi Format. Download Machine Learning books, Are you thinking of learning more about MachineLearning?(For Beginners)You will learn: Machine Learning Engineers earn on average $166,000 - become an ideal candidate withthis course! Master Machine Learning on Python, R &Scala Have a great intuition of many Machine Learning models Mathematical Foundation: Linear Algebra, Multivariate Calculus & Probability Theory Make powerful analysis Introduction to Programming Language Tools for Machine Learning Introduction to R/Python/Scala Introduction to MLlib (Apache Spark Libraries of Python Description: Interested in the field of Machine Learning? Then this book is for you! It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you would be well suited to tackle problems which enhance your interests using machine learning. The title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing mathematical concepts, specific algorithms, introduction to programming languages, best programming languages for Machine Learning and libraries of Python applied in Machine Learning, Download your copy now so you can get started on what is promising to be a most amazing future.


Large Scale Machine Learning With Spark

Large Scale Machine Learning with Spark PDF
Author: Md. Rezaul Karim
Publisher: Packt Publishing Ltd
ISBN: 1785883712
Size: 42.61 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 476
View: 5775

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Large Scale Machine Learning With Spark

by Md. Rezaul Karim, Large Scale Machine Learning With Spark Books available in PDF, EPUB, Mobi Format. Download Large Scale Machine Learning With Spark books, Discover everything you need to build robust machine learning applications with Spark 2.0 About This Book Get the most up-to-date book on the market that focuses on design, engineering, and scalable solutions in machine learning with Spark 2.0.0 Use Spark's machine learning library in a big data environment You will learn how to develop high-value applications at scale with ease and a develop a personalized design Who This Book Is For This book is for data science engineers and scientists who work with large and complex data sets. You should be familiar with the basics of machine learning concepts, statistics, and computational mathematics. Knowledge of Scala and Java is advisable. What You Will Learn Get solid theoretical understandings of ML algorithms Configure Spark on cluster and cloud infrastructure to develop applications using Scala, Java, Python, and R Scale up ML applications on large cluster or cloud infrastructures Use Spark ML and MLlib to develop ML pipelines with recommendation system, classification, regression, clustering, sentiment analysis, and dimensionality reduction Handle large texts for developing ML applications with strong focus on feature engineering Use Spark Streaming to develop ML applications for real-time streaming Tune ML models with cross-validation, hyperparameters tuning and train split Enhance ML models to make them adaptable for new data in dynamic and incremental environments In Detail Data processing, implementing related algorithms, tuning, scaling up and finally deploying are some crucial steps in the process of optimising any application. Spark is capable of handling large-scale batch and streaming data to figure out when to cache data in memory and processing them up to 100 times faster than Hadoop-based MapReduce. This means predictive analytics can be applied to streaming and batch to develop complete machine learning (ML) applications a lot quicker, making Spark an ideal candidate for large data-intensive applications. This book focuses on design engineering and scalable solutions using ML with Spark. First, you will learn how to install Spark with all new features from the latest Spark 2.0 release. Moving on, you'll explore important concepts such as advanced feature engineering with RDD and Datasets. After studying developing and deploying applications, you will see how to use external libraries with Spark. In summary, you will be able to develop complete and personalised ML applications from data collections,model building, tuning, and scaling up to deploying on a cluster or the cloud. Style and approach This book takes a practical approach where all the topics explained are demonstrated with the help of real-world use cases.