Interactive Visualization And Plotting With Julia
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Interactive Visualization And Plotting With Julia
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Author : Diego Javier Zea
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-08-29
Interactive Visualization And Plotting With Julia written by Diego Javier Zea and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-29 with Computers categories.
Represent and analyze data using Plots to find actionable insights using Julia programming Key FeaturesLearn to use static and interactive plots to explore data with JuliaBecome well versed with the various plotting attributes needed to customize your plotsCreate insightful and appealing plots using data interactions, animations, layouts, and themesBook Description The Julia programming language offers a fresh perspective into the data visualization field. Interactive Visualization and Plotting with Julia begins by introducing the Julia language and the Plots package. The book then gives a quick overview of the Julia plotting ecosystem to help you choose the best library for your task. In particular, you will discover the many ways to create interactive visualizations with its packages. You'll also leverage Pluto notebooks to gain interactivity and use them intensively through this book. You'll find out how to create animations, a handy skill for communication and teaching. Then, the book shows how to solve data analysis problems using DataFrames and various plotting packages based on the grammar of graphics. Furthermore, you'll discover how to create the most common statistical plots for data exploration. Also, you'll learn to visualize geographically distributed data, graphs and networks, and biological data. Lastly, this book will go deeper into plot customizations with Plots, Makie, and Gadfly—focusing on the former—teaching you to create plot themes, arrange multiple plots into a single figure, and build new plot types. By the end of this Julia book, you'll be able to create interactive and publication-quality static plots for data analysis and exploration tasks using Julia. What you will learnCreate interactive plots with Makie, Plots, Jupyter, and PlutoCreate standard statistical plots and visualize clustering resultsPlot geographically distributed and biological dataVisualize graphs and networks using GraphRecipes and GraphPlotsFind out how to draw and animate objects with Javis, Plots, and MakieDefine plot themes to reuse plot visual aspect customizationsArrange plots using Plots, Makie, and Gadfly layout systemsDefine new plot types and determine how Plots and Makie show objectsWho this book is for Data analysts looking to explore Julia's data visualization capabilities will find this book helpful, along with scientists and academics who want to generate and communicate knowledge and improve their teaching material. This data visualization book will also interest Julia programmers willing to delve into the language plotting ecosystem and improve their visualization skills. Basic programming knowledge is assumed — but the book will introduce you to Julia's important features. Familiarity with mathematical and statistical concepts will help you make the most of some of the chapters.
Ultimate Parallel And Distributed Computing With Julia For Data Science
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Author : Nabanita Dash
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-01-03
Ultimate Parallel And Distributed Computing With Julia For Data Science written by Nabanita Dash and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-03 with Computers categories.
Unleash Julia’s power: Code Your Data Stories, Shape Machine Intelligence! KEY FEATURES ● Comprehensive Learning Journey from fundamentals of Julia ML to advanced techniques. ● Immersive practical approach with real-world examples, exercises, and scenarios, ensuring immediate application of acquired knowledge. ● Delve into the unique features of Julia and unlock its true potential to excel in modern ML applications. DESCRIPTION This book takes you through a step-by-step learning journey, starting with the essentials of Julia's syntax, variables, and functions. You'll unlock the power of efficient data handling by leveraging Julia arrays and DataFrames.jl for insightful analysis. Develop expertise in both basic and advanced statistical models, providing a robust toolkit for deriving meaningful data-driven insights. The journey continues with machine learning proficiency, where you'll implement algorithms confidently using MLJ.jl and MLBase.jl, paving the way for advanced data-driven solutions. Explore the realm of Bayesian inference skills through practical applications using Turing.jl, enhancing your ability to extract valuable insights. The book also introduces crucial Julia packages such as Plots.jl for visualizing data and results. The handbook culminates in optimizing workflows with Julia's parallel and distributed computing capabilities, ensuring efficient and scalable data processing using Distributions.jl, Distributed.jl and SharedArrays.jl. This comprehensive guide equips you with the knowledge and practical insights needed to excel in the dynamic field of data science and machine learning. WHAT WILL YOU LEARN ● Master Julia ML Basics to gain a deep understanding of Julia's syntax, variables, and functions. ● Efficient Data Handling with Julia arrays and DataFrames for streamlined and insightful analysis. ● Develop expertise in both basic and advanced statistical models for informed decision-making through Statistical Modeling. ● Achieve Machine Learning Proficiency by confidently implementing ML algorithms using MLJ.jl and MLBase.jl. ● Apply Bayesian Inference Skills with Turing.jl for advanced modeling techniques. ● Optimize workflows using Julia's Parallel Processing Capabilities and Distributed Computing for efficient and scalable data processing. WHO IS THIS BOOK FOR? This book is designed to be a comprehensive and accessible companion for anyone eager to excel in machine learning and data analysis using Julia. Whether you are a novice or an experienced practitioner, the knowledge and skills imparted within these pages will empower you to navigate the complexities of modern data science with Julia. TABLE OF CONTENTS 1. Julia In Data Science Arena 2. Getting Started with Julia 3. Features Assisting Scaling ML Projects 4. Data Structures in Julia 5. Working With Datasets In Julia 6. Basics of Statistics 7. Probability Data Distributions 8. Framing Data in Julia 9. Working on Data in DataFrames 10. Visualizing Data in Julia 11. Introducing Machine Learning in Julia 12. Data and Models 13. Bayesian Statistics and Modeling 14. Parallel Computation in Julia 15. Distributed Computation in Julia Index
Hands On Data Science With Anaconda
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Author : Yuxing Yan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31
Hands On Data Science With Anaconda written by Yuxing Yan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-31 with Computers categories.
Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda Key Features -Use Anaconda to find solutions for clustering, classification, and linear regression -Analyze your data efficiently with the most powerful data science stack -Use the Anaconda cloud to store, share, and discover projects and libraries Book Description Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R. What you will learn Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda Use the package manager conda and discover, install, and use functionally efficient and scalable packages Get comfortable with heterogeneous data exploration using multiple languages within a project Perform distributed computing and use Anaconda Accelerate to optimize computational powers Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud Tackle advanced data prediction problems Who this book is for Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It’s also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected.
Web Development With Julia And Genie
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Author : Ivo Balbaert
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-11-29
Web Development With Julia And Genie written by Ivo Balbaert and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-29 with Computers categories.
Get a practical overview of web development in Julia and learn how to build MVC applications with a REST API, and an interactive data dashboard using the Genie web framework Key FeaturesA tutorial on web development from Julia expert, Ivo Balbaert and the creator of the Genie framework, Adrian SalceanuA step-by-step approach to building a complete web app with the Genie frameworkDevelop secure and fast web apps using server-side development on JuliaBook Description Julia's high-performance and scalability characteristics and its extensive number of packages for visualizing data make it an excellent fit for developing web apps, web services, and web dashboards. The two parts of this book provide complete coverage to build your skills in web development. First, you'll refresh your knowledge of the main concepts in Julia that will further be used in web development. Then, you'll use Julia's standard web packages and examine how the building blocks of the web such as TCP-IP, web sockets, HTTP protocol, and so on are implemented in Julia's standard library. Each topic is discussed and developed into code that you can apply in new projects, from static websites to dashboards. You'll also understand how to choose the right Julia framework for a project. The second part of the book talks about the Genie framework. You'll learn how to build a traditional to do app following the MVC design pattern. Next, you'll add a REST API to this project, including testing and documentation. Later, you'll explore the various ways of deploying an app in production, including authentication functionality. Finally, you'll work on an interactive data dashboard, making various chart types and filters. By the end of this book, you'll be able to build interactive web solutions on a large scale with a Julia-based web framework. What you will learnUnderstand how to make a web server with HTTP.jl and work with JSON data over the webDiscover how to build a static website with the Franklin frameworkExplore Julia web development frameworks and work with themUncover the Julia infrastructure for development, testing, package management, and deploymentDevelop an MVC web app with the Genie frameworkUnderstand how to add a REST API to a web appCreate an interactive data dashboard with charts and filtersTest, document, and deploy maintainable web applications using JuliaWho 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 web applications. The book helps you adopt Genie without any prior experience with the framework. Julia programming experience and a beginner-level understanding of web development concepts are required.
Julia For Data Science
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Author : Anshul Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30
Julia For Data Science written by Anshul Joshi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Explore the world of data science from scratch with Julia by your side About This Book An in-depth exploration of Julia's growing ecosystem of packages Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets Who This Book Is For This book is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to those competent in R and Python and wish to adopt Julia to improve their skills set in Data Science. It would be beneficial if the readers have a good background in statistics and computational mathematics. What You Will Learn Apply statistical models in Julia for data-driven decisions Understanding the process of data munging and data preparation using Julia Explore techniques to visualize data using Julia and D3 based packages Using Julia to create self-learning systems using cutting edge machine learning algorithms Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models Build a recommendation engine in Julia Dive into Julia's deep learning framework and build a system using Mocha.jl In Detail Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century). This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game. This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning. This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia. Style and approach This practical and easy-to-follow yet comprehensive guide will get you learning about Julia with respect to data science. Each topic is explained thoroughly and placed in context. For the more inquisitive, we dive deeper into the language and its use case. This is the one true guide to working with Julia in data science.
Learning Julia
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Author : Anshul Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-24
Learning Julia written by Anshul Joshi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-24 with Computers categories.
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.
Julia Programming Projects
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Author : Adrian Salceanu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-26
Julia Programming Projects written by Adrian Salceanu and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-26 with Computers categories.
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 FeaturesWork with powerful open-source libraries for data wrangling, analysis, and visualizationDevelop full-featured, full-stack web applications Learn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook 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 learnLeverage Julia's strengths, its top packages, and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real-life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis, visualization, and forecastingWho 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 Cookbook
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Author : Jalem Raj Rohit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30
Julia Cookbook written by Jalem Raj Rohit and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Over 40 recipes to get you up and running with programming using Julia About This Book Follow a practical approach to learn Julia programming the easy way Get an extensive coverage of Julia's packages for statistical analysis This recipe-based approach will help you get familiar with the key concepts in Juli Who This Book Is For This book is for data scientists and data analysts who are familiar with the basics of the Julia language. Prior experience of working with high-level languages such as MATLAB, Python, R, or Ruby is expected. What You Will Learn Extract and handle your data with Julia Uncover the concepts of metaprogramming in Julia Conduct statistical analysis with StatsBase.jl and Distributions.jl Build your data science models Find out how to visualize your data with Gadfly Explore big data concepts in Julia In Detail Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We'll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you'll see how to optimize data science programs with parallel computing and memory allocation. You'll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform. This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data. Style and approach This book has a recipe-based approach to help you grasp the concepts of Julia programming.
Statistics With Julia
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Author : Yoni Nazarathy
language : en
Publisher: Springer Nature
Release Date : 2021-09-04
Statistics With Julia written by Yoni Nazarathy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-04 with Computers categories.
This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.
Practical Data Science With Hadoop And Spark
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Author : Ofer Mendelevitch
language : en
Publisher: Addison-Wesley Professional
Release Date : 2016-12-08
Practical Data Science With Hadoop And Spark written by Ofer Mendelevitch and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-08 with Computers categories.
The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language