Statistics With Julia

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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.

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 Statistics

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Author : Mark Foster
language : en
Publisher: Mark Foster
Release Date :

Julia Programming For Statistics 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 Modern Statistical Analysis Are you ready to harness the speed and elegance of the Julia programming language for real-world statistics and data science applications? "Julia Programming for Statistics" is your complete, hands-on guide to mastering statistical methods and applications using one of today’s fastest-growing languages in data science. Whether you're a student, researcher, or data analyst looking to expand your skills, this book will take you from the fundamentals of Julia programming to advanced techniques in data science with Julia. Learn how to write powerful Julia code and apply it directly to real-world statistical problems. 🔍 What You'll Learn Inside: ✅ Foundations of Julia Programming – Understand the syntax and structure of the Julia computer language, with practical examples tailored for data analysis. ✅ Descriptive Statistics & Hypothesis Testing – Perform core statistical tasks using Julia data science packages like StatsBase. ✅ ANOVA, Linear & Multiple Regression – Learn essential and advanced statistical modeling techniques with clear, real-world examples. ✅ Bayesian Methods & Monte Carlo Simulations – Dive into probabilistic programming using Julia language deep learning and simulation tools. ✅ Big Data & Machine Learning Foundations – Discover how Julia data analytics meets performance demands in big data environments. ✅ Step-by-Step Tutorials – Hands-on walkthroughs designed for both beginners and experienced programmers, featuring Julia programming language examples that are easy to follow. 💡 Why Learn Statistics with Julia? The Julia language combines the ease of Python with the performance of C, making it perfect for high-performance statistical computing and machine learning. This book shows you how to leverage Julia’s modern ecosystem for efficient, scalable, and elegant solutions. Whether you're exploring Julia for data science, tackling complex models, or diving into Julia machine learning, this book gives you the tools and confidence to get the job done. 🎯 Who This Book is For: Aspiring data scientists looking for an edge in Julia coding Statisticians and analysts seeking performance and clarity Engineers, students, and researchers exploring data science in Julia Anyone interested in combining statistical analysis with a powerful, modern language Start Your Journey into Statistical Mastery with Julia Don’t settle for slow or outdated tools. Unlock the potential of Julia programming for statistics and level up your data science skills with a language built for the future. ➡️ Scroll up and click “Buy Now” to start learning Julia for statistical computing 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.

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

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!

Julia Programming For Statistics

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Author : MARK. FOSTER
language : en
Publisher: Independently Published
Release Date : 2025-07-24

Julia Programming For Statistics written by MARK. FOSTER and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.

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!

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

Journal Of Official Statistics

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Author :
language : en
Publisher:
Release Date : 2008

Journal Of Official Statistics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.