Search results for: julia-programming-projects

Julia Programming Projects

Author : Adrian Salceanu
File Size : 59.81 MB
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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 1 0 Programming Complete Reference Guide

Author : Ivo Balbaert
File Size : 89.81 MB
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Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features Leverage Julia's high speed and efficiency to build fast, efficient applications Perform supervised and unsupervised machine learning and time series analysis Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo Balbaert Julia Programming Projects by Adrian Salceanu What you will learn Create your own types to extend the built-in type system Visualize your data in Julia with plotting packages Explore the use of built-in macros for testing and debugging Integrate Julia with other languages such as C, Python, and MATLAB Analyze and manipulate datasets using Julia and DataFrames Develop and run a web app using Julia and the HTTP package Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Julia High Performance

Author : Avik Sengupta
File Size : 24.15 MB
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Design and develop high-performance programs in Julia 1.0 Key Features Learn the characteristics of high-performance Julia code Use the power of the GPU to write efficient numerical code Speed up your computation with the help of newly introduced shared memory multi-threading in Julia 1.0 Book Description Julia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you. The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster. By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs. What you will learn Understand how Julia code is transformed into machine code Measure the time and memory taken by Julia programs Create fast machine code using Julia's type information Define and call functions without compromising Julia's performance Accelerate your code via the GPU Use tasks and asynchronous IO for responsive programs Run Julia programs on large distributed clusters Who this book is for This book is for beginners and intermediate Julia programmers who are interested in high-performance technical programming. A basic knowledge of Julia programming is assumed.

Hands On Design Patterns and Best Practices with Julia

Author : Tom Kwong
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Design and develop high-performance, reusable, and maintainable applications using traditional and modern Julia patterns with this comprehensive guide Key Features Explore useful design patterns along with object-oriented programming in Julia 1.0 Implement macros and metaprogramming techniques to make your code faster, concise, and efficient Develop the skills necessary to implement design patterns for creating robust and maintainable applications Book Description Design patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications. Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages. By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development. What you will learn Master the Julia language features that are key to developing large-scale software applications Discover design patterns to improve overall application architecture and design Develop reusable programs that are modular, extendable, performant, and easy to maintain Weigh up the pros and cons of using different design patterns for use cases Explore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniques Who this book is for This book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications.

Julia 1 0 Programming Cookbook

Author : Bogumił Kamiński
File Size : 73.41 MB
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Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications. Key Features Address the core problems of programming in Julia with the most popular packages for common tasks Tackle issues while working with Databases and Parallel data processing with Julia Explore advanced features such as metaprogramming, functional programming, and user defined types Book Description Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data What you will learn Boost your code’s performance using Julia’s unique features Organize data in to fundamental types of collections: arrays and dictionaries Organize data science processes within Julia and solve related problems Scale Julia computations with cloud computing Write data to IO streams with Julia and handle web transfer Define your own immutable and mutable types Speed up the development process using metaprogramming Who this book is for This book is for developers who would like to enhance their Julia programming skills and would like to get some quick solutions to their common programming problems. Basic Julia programming knowledge is assumed.

Getting Started with Julia

Author : Ivo Balbaert
File Size : 85.34 MB
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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 High Performance Programming

Author : Ivo Balbaert
File Size : 69.22 MB
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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.

Managing Software Projects

Author : Frank F. Tsui
File Size : 77.20 MB
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Computer Architecture/Software Engineering

Julia for Machine Learning

Author : Zacharias Voulgaris
File Size : 78.53 MB
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Unleash the power of Julia for your machine learning tasks. We reveal why Julia is chosen for more and more data science and machine learning projects, including Julia’s ability to run algorithms at lightning speed. Next, we show you how to set up Julia and various IDEs such as Jupyter. Afterward, we explore key Julia libraries, which are useful for data science work, including packages related to visuals, data structures, and mathematical processes. After building a foundation in Julia, we dive into machine learning, with foundational concepts reinforced by Julia use cases. The use cases build upon each other, reaching the level where we code a machine learning model from scratch using Julia. All of these use cases are available in a series of Jupyter notebooks. After covering dimensionality reduction methods, we explore additional machine learning topics, such as parallelization and data engineering. Although knowing how to use Julia is essential, it is even more important to communicate our results to the business, which we cover next, including how to work efficiently with project stakeholders. Our Julia journey then ascends to the finer points, including improving machine learning transparency, reconciling machine learning with statistics, and continuing to innovate with Julia. The final chapters cover future trends in the areas of Julia, machine learning, and artificial intelligence. We explain machine learning and Bayesian Statistics hybrid systems, and Julia’s Gen language. We share many resources so you can continue to sharpen your Julia and machine learning skills. Each chapter concludes with a series of questions designed to reinforce that chapter’s material, with answers provided in an appendix. Other appendices include an extensive glossary, bridge packages between Julia and other programming languages, and an overview of three data science-related heuristics implemented in Julia, which aren’t in any of the existing packages.

Programming with Java

Author : Julia Case Bradley
File Size : 63.35 MB
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Java has become one of the leading development languages today. It plays a very important role in application development for business as well as a tool for Web programming. This Java text is designed primarily for business programming students. It assumes no prior programming experience and introduces students to the object-oriented approach from the very beginning. This text can be used for a first language course or for a more advanced programming course.

Evaluations of Illinois Weather Modification Projects of 1976 1980

Author : Stanley Alcide Changnon
File Size : 88.33 MB
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Programming in Visual Basic Net

Author : Julia Case Bradley
File Size : 51.67 MB
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Programming in Visual Basic Version 6 0

Author : Julia Case Bradley
File Size : 36.7 MB
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New to this Edition: added coverage of Object-Oriented-Programming, coverage of new features in Visual Basic 6.0, expanded and reorganized sections, coding standards conform to new Microsoft guidelines, and Visual Basic 6.0 working model.

The Practical Application of Project Planning by Network Techniques

Author : Mats Ogander
File Size : 20.6 MB
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Instructor s Manual to Accompany Programming in Visual Basic 6 0

Author : Julia Case Bradley, Anita C. Millspaugh
File Size : 46.69 MB
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QuickBASIC and QBASIC Using Modular Structure

Author : Julia Case Bradley
File Size : 57.9 MB
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Stressing good programming skills, this is intended for introductory programming courses using BASIC. It introduces the features of the language and includes an extensively revised chapter on graphics.

Master Visually Excel 2003 VBA Programming

Author : Julia Kelly
File Size : 51.17 MB
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This is a unique visual guide for those who want to take the next step in VBA expertise.

The Dynamics Newsletter

Author :
File Size : 68.91 MB
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Pedestrian Safety Improvement Program

Author : Offer Grembek
File Size : 50.4 MB
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Proceedings of the Fifth Industrial Engineering Research Conference

Author : Ronald G. Askin
File Size : 32.16 MB
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