Data Science With Julia
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Julia For Data Science
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Author : Zacharias Voulgaris
language : en
Publisher:
Release Date : 2016
Julia For Data Science written by Zacharias Voulgaris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Application software categories.
After covering the importance of Julia to the data science community and several essential data science principles, we start with the basics including how to install Julia and its powerful libraries. Many examples are provided as we illustrate how to leverage each Julia command, dataset, and function. Specialized script packages are introduced and described. Hands-on problems representative of those commonly encountered throughout the data science pipeline are provided, and we guide you in the use of Julia in solving them using published datasets. Many of these scenarios make use of existing packages and built-in functions, as we cover: An overview of the data science pipeline along with an example illustrating the key points, implemented in Julia Options for Julia IDEs Programming structures and functions Engineering tasks, such as importing, cleaning, formatting and storing data, as well as performing data preprocessing Data visualization and some simple yet powerful statistics for data exploration purposes Dimensionality reduction and feature evaluation Machine learning methods, ranging from unsupervised (different types of clustering) to supervised ones (decision trees, random forests, basic neural networks, regression trees, and Extreme Learning Machines) Graph analysis including pinpointing the connections among the various entities and how they can be mined for useful insights. Each chapter concludes with a series of questions and exercises to reinforce what you learned. The last chapter of the book will guide you in creating a data science application from scratch using Julia.
Julia Programming For Data Science
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Author : Mark Foster
language : en
Publisher: Mark Foster
Release Date :
Julia Programming For Data Science written by Mark Foster and has been published by Mark Foster this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
📊 Julia Programming for Data Science: From CSVs to Visual Insights Turn Raw Data Into Real Discoveries Using the Power of the Julia Programming Language Are you ready to break free from slow, bloated analytics tools and step into the future of data science? “Julia Programming for Data Science: From CSVs to Visual Insights” is the ultimate beginner-to-intermediate guide to mastering data science with Julia — the high-performance, modern solution for analysts, researchers, and machine learning developers. From reading raw CSV files to building beautiful visualizations and running powerful analytics, you’ll gain the skills you need to work smarter — not harder — using real-world Julia programming language examples and the best Julia data science packages like DataFrames.jl and Plots.jl. ✅ What You'll Learn Inside: 🔹 Import, Explore, and Clean Big Data — Fast Master the essentials of data science in Julia by importing CSVs, cleaning messy datasets, and exploring large datasets effortlessly. With the speed of Julia big data processing, you'll move from raw files to usable data in seconds. 🔹 Write Clean, Powerful Julia Code for Analytics Learn how the Julia code language simplifies complex tasks. This book teaches you how to perform filtering, transformations, aggregations, and summary statistics — all with readable and efficient Julia coding techniques. 🔹 Visualize Insights Like a Pro With Plots.jl and other top tools in the Julia statistics library, you’ll build insightful charts: from statistics histograms, scatter plots, and heatmaps, to advanced dashboards — making your data speak. 🔹 Get Started with Julia Statistical Analysis and Machine Learning Lay the groundwork for Julia statistical software, including multivariate statistics, standard deviation (std), and mode, while getting your first glimpse into Julia machine learning and Julia language deep learning. 🔹 Seamless Python Integration Already working in Python? Learn how calling Julia from Python can bring Julia’s speed and efficiency into your existing workflows without the need to start from scratch. 🎯 Perfect For: 📊 Beginners and professionals entering the world of Julia for data science 🧪 Researchers exploring Julia language statistics or scientific computing 🤖 ML engineers looking for high-speed alternatives to Python or R 📈 Analysts who need reliable, scalable solutions for data analytics with Julia 🎓 Students looking for a modern Julia data science tutorial with practical examples 🚀 Build Real Data Workflows That Deliver Results With Julia Programming for Data Science, you’re not just learning theory — you’re applying modern tools to real problems. From structured data analysis to stunning visual insights, this book gives you a complete walkthrough of the Julia programming language for today’s data-driven world. 🛒 Scroll up and get your copy now — and start mastering data science in Julia with confidence!
Data Science With Julia
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Author : Paul D. McNicholas
language : en
Publisher: CRC Press
Release Date : 2019-01-02
Data Science With Julia written by Paul D. McNicholas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-02 with Business & Economics categories.
"This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist."- Professor Charles Bouveyron, INRIA Chair in Data Science, Université Côte d’Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist." Professor Charles Bouveyron INRIA Chair in Data Science Université Côte d’Azur, Nice, France
Julia Programming For Data Analysi
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Author : Mark Foster
language : en
Publisher: Mark Foster
Release Date :
Julia Programming For Data Analysi written by Mark Foster and has been published by Mark Foster this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unlock the Power of Julia for Data Science, Machine Learning, and Big Data Projects Are you ready to dive into the world of data science with Julia? Whether you're a beginner eager to learn a new programming language or a data analyst looking to boost performance with modern tools, Julia Programming for Data Analysis is your ultimate hands-on guide. This practical book delivers a clear and accessible journey through the Julia programming language, designed specifically for data enthusiasts. You’ll master everything from writing your first lines of Julia code to deploying advanced machine learning models—without the steep learning curve. 💡 What You'll Learn: How to set up your environment and write your first Julia programming language examples A comprehensive Julia data science tutorial, perfect for beginners and transitioning professionals Practical techniques for manipulating, cleaning, and transforming data using the powerful DataFrames.jl package Importing and exporting datasets in popular formats like CSV, JSON, and even connecting to databases Data visualization strategies to create clear, impactful charts Step-by-step workflows for building machine learning models with Julia language machine learning tools How to harness Julia data science packages to streamline analysis and automation Deep dive into Julia language deep learning and Julia big data workflows for high-performance computing Whether you're exploring data science in Julia, looking for scalable Julia data analytics, or curious about how Julia coding compares to Python or R, this book delivers everything you need in one streamlined resource. Built for clarity and efficiency, this guide doesn’t just teach the Julia computer language—it helps you apply it with real-world data. With fully annotated examples, this is more than a tutorial—it's a practical roadmap to modern data-driven success. Why Choose Julia? Julia is fast, expressive, and designed for technical computing. For those working in data science, machine learning, or big data, Julia offers unparalleled performance without sacrificing readability. This book shows you how to take full advantage of that power. 📘 Perfect for: Aspiring and experienced data scientists Analysts looking to shift into Julia for data science Students and professionals seeking a better alternative for performance-critical data tasks Anyone curious about the future of Julia programming and high-speed analytics Don’t miss your chance to master the future of data analysis. Buy now and start your journey into Julia language success today!
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.
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.
Julia Programming For Data Science
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Author : Oliver Lucas, Jr
language : en
Publisher: Independently Published
Release Date : 2024-10-28
Julia Programming For Data Science written by Oliver Lucas, Jr and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-28 with Computers categories.
Julia Programming for Data Science: A Beginner-Friendly Approach Embark on a journey into the world of data science with Julia, a powerful and dynamic programming language designed for high-performance computing. This beginner-friendly guide will equip you with the skills and knowledge to tackle complex data analysis tasks with ease and efficiency. What you'll learn: Fundamentals of Julia: Master the basics of Julia programming, including data types, variables, operators, control flow, and functions. Data Wrangling and Manipulation: Learn to import, clean, transform, and analyze data using Julia's versatile data structures and libraries. Statistical Modeling and Machine Learning: Explore statistical concepts and implement machine learning algorithms with Julia's extensive ecosystem of packages. Data Visualization: Create compelling visualizations of your data using Julia's powerful plotting libraries. Real-world Applications: Apply your Julia skills to solve practical data science problems across various domains. Why choose this book? Clear and concise explanations: Complex concepts are broken down into digestible chunks, making it easy for beginners to grasp. Hands-on examples: Numerous practical examples and exercises reinforce your learning and help you apply Julia to real-world scenarios. Focus on data science: Tailored specifically for aspiring data scientists, this book covers the essential Julia tools and techniques for data analysis. Beginner-friendly approach: No prior programming experience is required. This book starts from the ground up and gradually introduces more advanced concepts. Unlock the power of Julia and become a proficient data scientist. Start your journey today!
Julia For Data Analysis
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Author : Bogumil Kaminski
language : en
Publisher: Simon and Schuster
Release Date : 2023-01-10
Julia For Data Analysis written by Bogumil Kaminski and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-10 with Computers categories.
Julia for Data Analysis teaches you how to handle core data analysis tasks with the Julia programming language. You'll start by reviewing language fundamentals you'll master essential data analysis skills through engaging examples. Along the way, you'll learn to easily transfer existing data pipelines to Julia.
Statistics With Julia
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Author : Yoni Nazarathy
language : en
Publisher:
Release Date : 2021
Statistics With Julia written by Yoni Nazarathy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with 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.
Julia Programming For Machine Learning
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Author : Mark Foster
language : en
Publisher: Mark Foster
Release Date :
Julia Programming For Machine Learning written by Mark Foster and has been published by Mark Foster this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
🔥 Unlock the Full Power of Julia for Machine Learning and AI Development Are you ready to master Julia programming for machine learning and take your AI projects to the next level? Whether you're a developer, data scientist, or beginner, this comprehensive Julia machine learning tutorial is your fast track to building smart, scalable models with unmatched speed and performance. Julia Programming for Machine Learning: Smart Models, Fast Execution dives deep into the world of differentiable programming in Julia, enabling you to create powerful models using cutting-edge tools like Flux.jl and MLJ.jl. From simple Julia coding for linear regression to advanced deep learning applications, you’ll gain practical, hands-on skills to build intelligent systems that run blazingly fast. 🚀 What You’ll Learn Inside: ✅ How to use the Julia programming language for machine learning, AI, and big data analytics ✅ Step-by-step Julia machine learning tutorials that walk you through real-world projects ✅ Master differentiable programming in Julia to boost your model’s learning efficiency ✅ Leverage Julia data science packages and libraries like MLJ.jl, Flux.jl, and more ✅ Build smart applications using a modern, high-performance Julia code language ✅ Explore the synergy between Julia and data science with practical examples ✅ Discover how Julia data science tools outperform Python and R in speed and scalability 💡 Who Is This Book For? 🧠 Beginners eager to dive into Julia programming for artificial intelligence 🧑💻 Developers looking to transition to the Julia computer language for faster model training 📊 Data scientists seeking a Julia data science tutorial that delivers clarity and hands-on results 🎓 Students exploring Julia courses or using a Julia online compiler for experimentation 🔎 Why Julia? Julia is not just another programming language. It combines the ease of Python, the speed of C, and the analytical power of R, making it perfect for data science with Julia and machine learning at scale. With growing popularity in big data, data analytics, and AI development, learning Julia now means future-proofing your skill set. 🛒 Don’t Miss Out — Make the Shift to Julia Today! Whether you're exploring Julia software for the first time or looking to enhance your existing ML pipeline, this book delivers the insights, tools, and confidence to succeed. It's time to code faster, think smarter, and build better—with Julia. 📘 Grab your copy of Julia Programming for Machine Learning now and start building intelligent, high-performance models today!