Getting Started with Julia

Author: Ivo Balbaert

Publisher: Packt Publishing Ltd

ISBN: 1783284803

Category: Computers

Page: 214

View: 8491

This book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby.

Julia Programming Projects

Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web

Author: Adrian Salceanu

Publisher: Packt Publishing Ltd

ISBN: 1788297253

Category: Computers

Page: 500

View: 7635

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features Work with powerful open-source libraries for data wrangling, analysis, and visualization Develop full-featured, full-stack web applications Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn Leverage Julia's strengths, its top packages, and main IDE options Analyze and manipulate datasets using Julia and DataFrames Write complex code while building real-life Julia applications Develop and run a web app using Julia and the HTTP package Build a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithms Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Julia: High Performance Programming

Author: Ivo Balbaert,Avik Sengupta,Malcolm Sherrington

Publisher: Packt Publishing Ltd

ISBN: 1787126102

Category: Computers

Page: 697

View: 2019

Leverage the power of Julia to design and develop high performing programs About This Book Get to know the best techniques to create blazingly fast programs with Julia Stand out from the crowd by developing code that runs faster than your peers' code Complete an extensive data science project through the entire cycle from ETL to analytics and data visualization Who This Book Is For This learning path is for data scientists and for all those who work in technical and scientific computation projects. It will be great for Julia developers who are interested in high-performance technical computing. This learning path assumes that you already have some basic working knowledge of Julia's syntax and high-level dynamic languages such as MATLAB, R, Python, or Ruby. What You Will Learn Set up your Julia environment to achieve the highest productivity Solve your tasks in a high-level dynamic language and use types for your data only when needed Apply Julia to tackle problems concurrently and in a distributed environment Get a sense of the possibilities and limitations of Julia's performance Use Julia arrays to write high performance code Build a data science project through the entire cycle of ETL, analytics, and data visualization Display graphics and visualizations to carry out modeling and simulation in Julia Develop your own packages and contribute to the Julia Community In Detail In this learning path, you will learn to use an interesting and dynamic programming language—Julia! You will get a chance to tackle your numerical and data problems with Julia. You'll begin the journey by setting up a running Julia platform before exploring its various built-in types. We'll then move on to the various functions and constructs in Julia. We'll walk through the two important collection types—arrays and matrices in Julia. You will dive into how Julia uses type information to achieve its performance goals, and how to use multiple dispatch to help the compiler emit high performance machine code. You will see how Julia's design makes code fast, and you'll see its distributed computing capabilities. By the end of this learning path, you will see how data works using simple statistics and analytics, and you'll discover its high and dynamic performance—its real strength, which makes it particularly useful in highly intensive computing tasks. 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: Getting Started with Julia by Ivo Balvaert Julia High Performance by Avik Sengupta Mastering Julia by Malcolm Sherrington Style and approach This hands-on manual will give you great explanations of the important concepts related to Julia programming.

Einführung in Python

Author: Mark Lutz,David Ascher,Dinu C. Gherman

Publisher: O'Reilly Germany

ISBN: 3897214881

Category: Python (Computer program language)

Page: 624

View: 8929

Learning Julia

Build high-performance applications for scientific computing

Author: Anshul Joshi,Rahul Lakhanpal

Publisher: Packt Publishing Ltd

ISBN: 1785885367

Category: Computers

Page: 316

View: 3849

Learn Julia language for data science and data analytics About This Book Set up Julia's environment and start building simple programs Explore the technical aspects of Julia and its potential when it comes to speed and data processing Write efficient and high-quality code in Julia Who This Book Is For This book allows existing programmers, statisticians and data scientists to learn the Julia and take its advantage while building applications with complex numerical and scientific computations. Basic knowledge of mathematics is needed to understand the various methods that will be used or created in the book to exploit the capabilities for which Julia is made. What You Will Learn Understand Julia's ecosystem and create simple programs Master the type system and create your own types in Julia Understand Julia's type system, annotations, and conversions Define functions and understand meta-programming and multiple dispatch Create graphics and data visualizations using Julia Build programs capable of networking and parallel computation Develop real-world applications and use connections for RDBMS and NoSQL Learn to interact with other programming languages–C and Python—using Julia In Detail Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain. Style and approach This book demonstrates the basics of Julia along with some data structures and testing tools that will give you enough material to get started with the language from an application standpoint.

Die Kunst der JavaScript-Programmierung

Eine moderne Einführung in die Sprache des Web

Author: Marijn Haverbeke

Publisher: dpunkt.verlag

ISBN: 3864911915

Category: Computers

Page: 240

View: 4126

Das Buch ist eine Einführung in JavaScript, die sich auf gute Programmiertechniken konzentriert. Der Autor lehrt den Leser, wie man die Eleganz und Präzision von JavaScript nutzt, um browserbasierte Anwendungen zu schreiben. Das Buch beginnt mit den Grundlagen der Programmierung - Variablen, Kontrollstrukturen, Funktionen und Datenstrukturen -, dann geht es auf komplexere Themen ein, wie die funktionale und objektorientierte Programmierung, reguläre Ausdrücke und Browser-Events. Unterstützt von verständlichen Beispielen wird der Leser rasch die Sprache des Web fließend 'sprechen' können.

Programmieren mit Ruby

Author: David Thomas,Andrew Hunt

Publisher: Pearson Deutschland GmbH

ISBN: 9783827319654


Page: 681

View: 3195

Beginning Julia Programming

For Engineers and Scientists

Author: Sandeep Nagar

Publisher: Apress

ISBN: 1484231716

Category: Computers

Page: 351

View: 737

Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll cover, includes working with complex numbers, rational and irrational numbers, rings, and fields. Beginning Julia Programming takes you beyond these basics to harness Julia’s powerful features for mathematical functions in Julia, arrays for matrix operations, plotting, and more. Along the way, you also learn how to manage strings, write functions, work with control flows, and carry out I/O to implement and leverage the mathematics needed for your data science and analysis projects. "Julia walks like Python and runs like C". This phrase explains why Julia is quickly growing as the most favored option for data analytics and numerical computation. After reading and using this book, you'll have the essential knowledge and skills to build your first Julia-based application. What You'll Learn Obtain core skills in Julia Apply Julia in engineering and science applications Work with mathematical functions in Julia Use arrays, strings, functions, control flow, and I/O in Julia Carry out plotting and display basic graphics Who This Book Is For Those who are new to Julia; experienced users may also find this helpful as a reference.

Routineaufgaben mit Python automatisieren

Praktische Programmierlösungen für Einsteiger

Author: Al Sweigart

Publisher: dpunkt.verlag

ISBN: 3864919932

Category: Computers

Page: 576

View: 9162

Wenn Sie jemals Stunden damit verbracht haben, Dateien umzubenennen oder Hunderte von Tabelleneinträgen zu aktualisieren, dann wissen Sie, wie stumpfsinnig manche Tätigkeiten sein können. Wie wäre es, den Computer dazu zu bringen, diese Arbeiten zu übernehmen? In diesem Buch lernen Sie, wie Sie mit Python Aufgaben in Sekundenschnelle erledigen können, die sonst viel Zeit in Anspruch nehmen würden. Programmiererfahrung brauchen Sie dazu nicht: Wenn Sie einmal die Grundlagen gemeistert haben, werden Sie Python-Programme schreiben, die automatisch alle möglichen praktischen Aufgaben für Sie abarbeiten: • eine oder eine Vielzahl von Dateien nach Texten durchsuchen • Dateien und Ordner erzeugen, aktualisieren, verschieben und umbenennen • das Web durchsuchen und Inhalte herunterladen • Excel-Dateien aktualisieren und formatieren • PDF-Dateien teilen, zusammenfügen, mit Wasserzeichen versehen und verschlüsseln • Erinnerungsmails und Textnachrichten verschicken • Online-Formulare ausfüllen Schritt-für-Schritt-Anleitungen führen Sie durch jedes Programm und Übungsaufgaben am Ende jedes Kapitels fordern Sie dazu auf, die Programme zu verbessern und Ihre Fähigkeiten auf ähnliche Problemstellungen zu richten. Verschwenden Sie nicht Ihre Zeit mit Aufgaben, die auch ein gut dressierter Affe erledigen könnte. Bringen Sie Ihren Computer dazu, die langweilige Arbeit zu machen!


Praktische Tipps für Fortgeschrittene

Author: Dan Bader

Publisher: dpunkt.verlag

ISBN: 3960886004

Category: Computers

Page: 210

View: 5042

Dieses Buch soll aus dir einen besseren Python-Programmierer machen.Um den größten Nutzen aus diesem Buch zu ziehen, solltest du bereits über Python-Kenntnisse verfügen, die du erweitern möchtest. Am besten ist es, wenn du schon eine Weile in Python programmierst und bereit bist, in die Tiefe zu gehen, deine Kenntnisse abzurunden und deinen Code pythonischer zu machen.Wenn du dich fragst, welche weniger bekannten Teile in Python du kennen solltest, gibt dir dieses Buch eine Roadmap an die Hand. Entdecke coole und gleichzeitig praktische Python-Tricks, mit denen du beim nächsten Code Review der Hit bist.Wenn du Erfahrung mit älteren Versionen von Python hast, wird dich das Buch mit modernen Mustern und Funktionen vertraut machen, die in Python 3 eingeführt wurden.Dieses Buch ist aber auch hervorragend für dich geeignet, wenn du schon Erfahrungen mit anderen Programmiersprachen hast und dich schnell in Python einarbeiten möchtest. Du wirst hier einen wahren Schatz an praktischen Tipps und Entwurfsmustern finden, die dir helfen, ein erfolgreicher Python-Programmierer zu werden.

Datenanalyse mit Python

Auswertung von Daten mit Pandas, NumPy und IPython

Author: Wes McKinney

Publisher: O'Reilly

ISBN: 3960102143

Category: Computers

Page: 542

View: 2931

Erfahren Sie alles über das Manipulieren, Bereinigen, Verarbeiten und Aufbereiten von Datensätzen mit Python: Aktualisiert auf Python 3.6, zeigt Ihnen dieses konsequent praxisbezogene Buch anhand konkreter Fallbeispiele, wie Sie eine Vielzahl von typischen Datenanalyse-Problemen effektiv lösen. Gleichzeitig lernen Sie die neuesten Versionen von pandas, NumPy, IPython und Jupyter kennen.Geschrieben von Wes McKinney, dem Begründer des pandas-Projekts, bietet Datenanalyse mit Python einen praktischen Einstieg in die Data-Science-Tools von Python. Das Buch eignet sich sowohl für Datenanalysten, für die Python Neuland ist, als auch für Python-Programmierer, die sich in Data Science und Scientific Computing einarbeiten wollen. Daten und zugehöriges Material des Buchs sind auf GitHub verfügbar.Aus dem Inhalt:Nutzen Sie die IPython-Shell und Jupyter Notebook für das explorative ComputingLernen Sie Grundfunktionen und fortgeschrittene Features von NumPy kennenSetzen Sie die Datenanalyse-Tools der pandasBibliothek einVerwenden Sie flexible Werkzeuge zum Laden, Bereinigen, Transformieren, Zusammenführen und Umformen von DatenErstellen Sie interformative Visualisierungen mit matplotlibWenden Sie die GroupBy-Mechanismen von pandas an, um Datensätzen zurechtzuschneiden, umzugestalten und zusammenzufassenAnalysieren und manipulieren Sie verschiedenste Zeitreihen-DatenFür diese aktualisierte 2. Auflage wurde der gesamte Code an Python 3.6 und die neuesten Versionen der pandas-Bibliothek angepasst. Neu in dieser Auflage: Informationen zu fortgeschrittenen pandas-Tools sowie eine kurze Einführung in statsmodels und scikit-learn.

Fundamental Statistical Inference

A Computational Approach

Author: Marc S. Paolella

Publisher: John Wiley & Sons

ISBN: 1119417872

Category: Mathematics

Page: 584

View: 7834

A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.

Introduction to Quantitative Macroeconomics Using Julia

From Basic to State-of-the-Art Computational Techniques

Author: Petre Caraiani

Publisher: Academic Press

ISBN: 0128135123

Category: Business & Economics

Page: 238

View: 8949

Introduction to Quantitative Macroeconomics Using Julia: From Basic to State-of-the-Art Computational Techniques facilitates access to fundamental techniques in computational and quantitative macroeconomics. It focuses on the recent and very promising software, Julia, which offers a MATLAB-like language at speeds comparable to C/Fortran, also discussing modeling challenges that make quantitative macroeconomics dynamic, a key feature that few books on the topic include for macroeconomists who need the basic tools to build, solve and simulate macroeconomic models. This book neatly fills the gap between intermediate macroeconomic books and modern DSGE models used in research. Combines an introduction to Julia, with the specific needs of macroeconomic students who are interested in DSGE models and PhD students and researchers interested in building DSGE models Teaches fundamental techniques in quantitative macroeconomics by introducing theoretical elements of key macroeconomic models and their potential algorithmic implementations Exposes researchers working in macroeconomics to state-of-the-art computational techniques for simulating and solving DSGE models

Mit Java programmieren lernen für Dummies

Author: Barry A. Burd

Publisher: John Wiley & Sons

ISBN: 3527691898

Category: Computers

Page: 463

View: 2660

Steigen Sie mit diesem Buch in die Welt des Programmierens ein und zwar mit der beliebten Programmiersprache Java! Schritt fï¿1⁄2r Schritt werden Sie mit den Grundlagen, wie zum Beispiel Variablen, Schleifen und objektorientierter Programmierung, vertraut gemacht, probieren viele anschauliche Beispiele aus und schreiben Ihr erstes eigenes Programm. Dieses Buch steht Ihnen bei allen Herausforderungen jederzeit mit hilfreichen Tipps und Lï¿1⁄2sungsvorschlï¿1⁄2gen zur Seite, sodass Sie fï¿1⁄2r Ihren Weg zum Programmierer optimal gerï¿1⁄2stet sind!

Die C++-Programmiersprache

Author: Bjarne Stroustrup

Publisher: Pearson Deutschland GmbH

ISBN: 9783827316608

Category: C+

Page: 1068

View: 2767

R in a Nutshell

Author: Joseph Adler

Publisher: O'Reilly Germany

ISBN: 3897216507

Category: Computers

Page: 768

View: 8427

Wozu sollte man R lernen? Da gibt es viele Gründe: Weil man damit natürlich ganz andere Möglichkeiten hat als mit einer Tabellenkalkulation wie Excel, aber auch mehr Spielraum als mit gängiger Statistiksoftware wie SPSS und SAS. Anders als bei diesen Programmen hat man nämlich direkten Zugriff auf dieselbe, vollwertige Programmiersprache, mit der die fertigen Analyse- und Visualisierungsmethoden realisiert sind – so lassen sich nahtlos eigene Algorithmen integrieren und komplexe Arbeitsabläufe realisieren. Und nicht zuletzt, weil R offen gegenüber beliebigen Datenquellen ist, von der einfachen Textdatei über binäre Fremdformate bis hin zu den ganz großen relationalen Datenbanken. Zudem ist R Open Source und erobert momentan von der universitären Welt aus die professionelle Statistik. R kann viel. Und Sie können viel mit R machen – wenn Sie wissen, wie es geht. Willkommen in der R-Welt: Installieren Sie R und stöbern Sie in Ihrem gut bestückten Werkzeugkasten: Sie haben eine Konsole und eine grafische Benutzeroberfläche, unzählige vordefinierte Analyse- und Visualisierungsoperationen – und Pakete, Pakete, Pakete. Für quasi jeden statistischen Anwendungsbereich können Sie sich aus dem reichen Schatz der R-Community bedienen. Sprechen Sie R! Sie müssen Syntax und Grammatik von R nicht lernen – wie im Auslandsurlaub kommen Sie auch hier gut mit ein paar aufgeschnappten Brocken aus. Aber es lohnt sich: Wenn Sie wissen, was es mit R-Objekten auf sich hat, wie Sie eigene Funktionen schreiben und Ihre eigenen Pakete schnüren, sind Sie bei der Analyse Ihrer Daten noch flexibler und effektiver. Datenanalyse und Statistik in der Praxis: Anhand unzähliger Beispiele aus Medizin, Wirtschaft, Sport und Bioinformatik lernen Sie, wie Sie Daten aufbereiten, mithilfe der Grafikfunktionen des lattice-Pakets darstellen, statistische Tests durchführen und Modelle anpassen. Danach werden Ihnen Ihre Daten nichts mehr verheimlichen.

Learn Red – Fundamentals of Red

Get up and running with the Red language for full-stack development

Author: Ivo Balbaert

Publisher: Packt Publishing Ltd

ISBN: 1789133653

Category: Computers

Page: 252

View: 4112

Discover how to use the next-generation language Red for full-stack development, from systems coding over user-interfaces to blockchain programming Key Features Explore the latest features of Red to build scalable, fast, and secure applications Learn graphical programming and build highly sophisticated reactive applications Get familiar with the specific concepts and techniques of Red development, like working with series, viewing code as data, and using dialects. Book Description A key problem of software development today is software bloat, where huge toolchains and development environments are needed in software coding and deployment. Red significantly reduces this bloat by offering a minimalist but complete toolchain. This is the first introductory book about it, and it will get you up and running with Red as quickly as possible. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Red to explore its wide and ever-growing package ecosystem and also for experienced developers who want to add Red to their skill set. The book presents the fundamentals of programming in Red and in-depth informative examples using a step-by-step approach. You will be taken through concepts and examples such as doing simple metaprogramming, functions, collections, GUI applications, and more. By the end of the book, you will be fully equipped to start your own projects in Red. What you will learn Set up your Red environment to achieve the highest productivity Get grounded in Red, gaining experience and insight through many examples and exercises Build simple, compact, and portable applications Analyze streams of data through Parse Compose GUI applications with View and Draw Get prepared for smart contract blockchain programming in Red Who this book is for This book is for software developers and architects who want to learn Red because of its conciseness, flexibility, and expressiveness, and more specifically for its possibilities in GUI apps and blockchain / smart contracts programming. Some knowledge of the basic concepts and experience of any programming language is assumed.

Gesang der Erde


Author: Barbara Wood

Publisher: S. Fischer Verlag

ISBN: 3104002355

Category: Fiction

Page: 576

View: 8770

Hoshi’tiwa gehört zum Clan der Schildkröte, der friedlich in den roten Felsencanyons lebt. Da wird die junge Frau von den Kriegern des Großen Herrschers entführt. Sie soll die magischen Tonkrüge fertigen, die den Regen bringen. Versagt sie, ist ihr Leben verwirkt. Jahrhunderte später forscht der Arzt Faraday Hightower nach der versunkenen Indianerkultur. Er will das Geheimnis des Tonkruges lösen...

Das Beste an JavaScript

Author: Douglas Crockford,Peter Klicman

Publisher: O'Reilly Germany

ISBN: 3897218763

Category: JavaScript (Computer program language)

Page: 163

View: 9491