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Julia Cookbook

Book Description

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 recipe-based approach will help you get familiar with the key concepts in Juli

    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.

    Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the code file.

    Table of Contents

    1. Julia Cookbook
      1. Julia Cookbook
      2. Credits
      3. About the Author
      4. About the Reviewer
      5. www.PacktPub.com
        1. eBooks, discount offers, and more
          1. Why subscribe?
          2. Free access for Packt account holders
      6. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Sections
          1. Getting ready
          2. How to do it…
          3. How it works…
          4. There's more…
          5. See also
        5. Conventions
        6. Reader feedback
        7. Customer support
          1. Errata
          2. Piracy
          3. Questions
      7. 1. Extracting and Handling Data
        1. Introduction
        2. Why should we use Julia for data science?
        3. Handling data with CSV files
          1. Getting ready
          2. How to do it...
        4. Handling data with TSV files
          1. Getting ready
          2. How to do it...
        5. Working with databases in Julia
          1. Getting ready
          2. How to do it...
            1. MySQL
          3. PostgreSQL
          4. There's more...
            1. MySQL
            2. PostgreSQL
            3. SQLite
        6. Interacting with the Web
          1. Getting ready
          2. How to do it...
            1. GET request
          3. There's more...
      8. 2. Metaprogramming
        1. Introduction
        2. Representation of a Julia program
          1. Getting ready
          2. How to do it...
          3. How it works...
          4. There's more
        3. Symbols and expressions
        4. Symbols
          1. Getting ready
          2. How to do it...
          3. How it works...
          4. There's more
        5. Quoting
          1. How to do it...
          2. How it works...
        6. Interpolation
          1. How to do it...
          2. How it works...
          3. There's more
        7. The Eval function
          1. Getting ready
          2. How to do it...
          3. How it works...
        8. Macros
          1. Getting ready
          2. How to do it...
          3. How it works...
        9. Metaprogramming with DataFrames
          1. Getting ready
          2. How to do it...
          3. How it works...
      9. 3. Statistics with Julia
        1. Introduction
        2. Basic statistics concepts
          1. Getting ready
          2. How to do it...
          3. How it works...
        3. Descriptive statistics
          1. Getting ready
          2. How to do it...
          3. How it works...
        4. Deviation metrics
          1. Getting ready
          2. How to do it...
          3. How it works...
        5. Sampling
          1. Getting ready
          2. How to do it...
          3. How it works...
        6. Correlation analysis
          1. Getting ready
          2. How to do it...
          3. How it works...
      10. 4. Building Data Science Models
        1. Introduction
        2. Dimensionality reduction
          1. Getting ready
          2. How to do it...
          3. How it works...
        3. Linear discriminant analysis
          1. Getting ready
          2. How to do it...
          3. How it works...
        4. Data preprocessing
          1. Getting ready
          2. How to do it...
          3. How it works...
        5. Linear regression
          1. Getting ready
          2. How to do it...
          3. How it works...
        6. Classification
          1. Getting ready
          2. How to do it...
          3. How it works...
        7. Performance evaluation and model selection
          1. Getting ready
          2. How to do it...
          3. How it works...
        8. Cross validation
          1. Getting ready
          2. How to do it...
          3. How it works...
        9. Distances
          1. Getting ready
          2. How to do it...
          3. How it works...
        10. Distributions
          1. Getting ready
          2. How to do it...
          3. How it works...
        11. Time series analysis
          1. Getting ready
          2. How to do it...
          3. How it works...
      11. 5. Working with Visualizations
        1. Introduction
        2. Plotting basic arrays
          1. Getting ready
          2. How to do it...
          3. How it works...
        3. Plotting dataframes
          1. Getting ready
          2. How to do it...
          3. How it works...
        4. Plotting functions
          1. Getting ready
          2. How to do it...
          3. How it works...
        5. Exploratory data analytics through plots
          1. Getting ready
          2. How to do it...
          3. How it works...
        6. Line plots
          1. Getting ready
          2. How to do it...
          3. How it works...
        7. Scatter plots
          1. Getting ready
          2. How to do it...
          3. How it works...
        8. Histograms
          1. Getting ready
          2. How to do it...
          3. How it works...
        9. Aesthetic customizations
          1. Getting ready
          2. How to do it...
          3. How it works…
      12. 6. Parallel Computing
        1. Introduction
        2. Basic concepts of parallel computing
          1. Getting ready
          2. How to do it...
          3. How it works...
        3. Data movement
          1. Getting ready
          2. How to do it...
          3. How it works...
        4. Parallel maps and loop operations
          1. Getting ready
          2. How to do it...
          3. How it works...
        5. Channels
          1. Getting ready
          2. How to do it...