Julia 1.0 Programming Cookbook PDF Download
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Author: Bogumił Kamiński
Publisher: Packt Publishing Ltd
ISBN: 1788998820
Category : Computers
Languages : en
Pages : 451
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Book Description
Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications. Key FeaturesAddress the core problems of programming in Julia with the most popular packages for common tasksTackle issues while working with Databases and Parallel data processing with JuliaExplore advanced features such as metaprogramming, functional programming, and user defined typesBook 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 learnBoost your code’s performance using Julia’s unique featuresOrganize data in to fundamental types of collections: arrays and dictionariesOrganize data science processes within Julia and solve related problemsScale Julia computations with cloud computingWrite data to IO streams with Julia and handle web transferDefine your own immutable and mutable typesSpeed up the development process using metaprogrammingWho 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.
Author: Bogumił Kamiński
Publisher: Packt Publishing Ltd
ISBN: 1788998820
Category : Computers
Languages : en
Pages : 451
Get Book
Book Description
Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications. Key FeaturesAddress the core problems of programming in Julia with the most popular packages for common tasksTackle issues while working with Databases and Parallel data processing with JuliaExplore advanced features such as metaprogramming, functional programming, and user defined typesBook 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 learnBoost your code’s performance using Julia’s unique featuresOrganize data in to fundamental types of collections: arrays and dictionariesOrganize data science processes within Julia and solve related problemsScale Julia computations with cloud computingWrite data to IO streams with Julia and handle web transferDefine your own immutable and mutable typesSpeed up the development process using metaprogrammingWho 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.
Author: Nabanita Dash
Publisher: Orange Education Pvt Ltd
ISBN: 9391246869
Category : Computers
Languages : en
Pages : 552
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Book Description
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
Author: David Strauss
Publisher: JHU Press
ISBN: 1421429063
Category : History
Languages : en
Pages : 349
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Book Description
Before Julia Child’s warbling voice and towering figure burst into America’s homes, a gourmet food movement was already sweeping the nation. Setting the Table for Julia Child considers how the tastes and techniques cultivated at dining clubs and in the pages of Gourmet magazine helped prepare many affluent Americans for Child’s lessons in French cooking. David Strauss argues that Americans’ appetite for haute cuisine had been growing ever since the repeal of Prohibition. Dazzled by visions of the good life presented in luxury lifestyle magazines and by the practices of the upper class, who adopted European taste and fashion, upper-middle-class Americans increasingly populated the gourmet movement. In the process, they came to appreciate the cuisine created by France's greatest chef, Auguste Escoffier. Strauss’s impressive archival research illuminates themes—gender, class, consumerism, and national identity—that influenced the course of gourmet dining in America. He also points out how the work of painters and fine printers—reproduced here—called attention to the aesthetic of dining, a vision that heightened one’s anticipation of a gratifying experience. In the midst of this burgeoning gourmet food movement Child found her niche. The movement may have introduced affluent Americans to the pleasure of French cuisine years before Julia Child, but it was Julia’s lessons that expanded the audience for gourmet dining and turned lovers of French cuisine into cooks.
Author: Martin H. Trauth
Publisher: Springer Nature
ISBN: 3031077199
Category : Science
Languages : en
Pages : 463
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Book Description
Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.
Author: Shiju Varghese
Publisher: Apress
ISBN: 148421188X
Category : Computers
Languages : en
Pages : 248
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Book Description
Solve your Go problems using a problem-solution approach. Each recipe is a self-contained answer to a practical programming problem in Go. Go Recipes contains recipes that deal with the fundamentals of Go, allowing you to build simple, reliable, and efficient software. Other topics include working with data using modern NoSQL databases such as MongoDB and RethinkDB. The book provides in-depth guidance for building highly scalable backend APIs in Go for your mobile client applications and web client applications. All this means that you’ll be able to write programs that get the most out of multicore and networked machines, using Go’s novel type system that enables flexible and modular program construction. You'll see how to test your Go applications so they are ready for deployment, as well as learning how to write HTTP servers to offer you maximum flexibility when dealing with remote clients. What You'll Learn Work with the core fundamentals of Go Persist data into NoSQL databases Build scalable backend APIs Test your Go applications Create HTTP web servers in Go Who This Book Is For Experienced programmers who have some or no prior experience with Go.
Author:
Publisher: Carson-Dellosa Publishing
ISBN: 1483814149
Category : Juvenile Nonfiction
Languages : en
Pages : 160
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Book Description
Strong reading skills are the basis of school success, and Spectrum Reading for grade 7 will help children triumph over language arts and beyond. This standards-based workbook uses engaging texts to support understanding story structure, key ideas, details, and knowledge integration. Spectrum Reading will help your child improve their reading habits and strengthen their ability to understand and analyze text. This best-selling series is a favorite of parents and teachers because it is carefully designed to be both effective and engaging—the perfect building blocks for a lifetime of learning.
Author: Kennan Ferguson
Publisher: University of Pennsylvania Press
ISBN: 0812252268
Category : Political Science
Languages : en
Pages : 160
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Book Description
An original and eclectic view of cookbooks as political acts Cookbooks are not political in conventional ways. They neither proclaim, as do manifestos, nor do they forbid, as do laws. They do not command agreement, as do arguments, and their stipulations often lack specificity — cook "until browned." Yet, as repositories of human taste, cookbooks transmit specific blends of flavor, texture, and nutrition across space and time. Cookbooks both form and reflect who we are. In Cookbook Politics, Kennan Ferguson explores the sensual and political implications of these repositories, demonstrating how they create nations, establish ideologies, shape international relations, and structure communities. Cookbook Politics argues that cookbooks highlight aspects of our lives we rarely recognize as political—taste, production, domesticity, collectivity, and imagination—and considers the ways in which cookbooks have or do politics, from the most overt to the most subtle. Cookbooks turn regional diversity into national unity, as Pellegrino Artusi's Science in the Kitchen and the Art of Eating Well did for Italy in 1891. Politically affiliated organizations compile and sell cookbooks—for example, the early United Nations published The World's Favorite Recipes. From the First Baptist Church of Midland, Tennessee's community cookbook, to Julia Child's Mastering the Art of French Cooking, to the Italian Futurists' proto-fascist guide to food preparation, Ferguson demonstrates how cookbooks mark desires and reveal social commitments: your table becomes a representation of who you are. Authoritative, yet flexible; collective, yet individualized; cooperative, yet personal—cookbooks invite participation, editing, and transformation. Created to convey flavor and taste across generations, communities, and nations, they enact the continuities and changes of social lives. Their functioning in the name of creativity and preparation—with readers happily consuming them in similar ways—makes cookbooks an exemplary model for democratic politics.
Author: Jane K. Glenn
Publisher: Bloomsbury Publishing USA
ISBN: 1440862109
Category : Social Science
Languages : en
Pages : 430
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Book Description
This volume explores our cultural celebration of food, blending lobster festivals, politicians' roadside eats, reality show "chef showdowns," and gravity-defying cakes into a deeper exploration of why people find so much joy in eating. In 1961, Julia Child introduced the American public to an entirely new, joy-infused approach to cooking and eating food. In doing so, she set in motion a food renaissance that is still in full bloom today. Over the last six decades, food has become an increasingly more diverse, prominent, and joyful point of cultural interest. The Joy of Eating discusses in detail the current golden age of food in contemporary American popular culture. Entries explore the proliferation of food-themed television shows, documentaries, and networks; the booming popularity of celebrity chefs; unusual, exotic, decadent, creative, and even mundane food trends; and cultural celebrations of food, such as in festivals and music. The volume provides depth and academic gravity by tying each entry into broader themes and larger contexts (in relation to a food-themed reality show, for example, discussing the show's popularity in direct relation to a significant economic event), providing a brief history behind popular foods and types of cuisines and tracing the evolution of our understanding of diet and nutrition, among other explications.
Author: Max Kuhn
Publisher: "O'Reilly Media, Inc."
ISBN: 1492096458
Category : Computers
Languages : en
Pages : 384
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Book Description
Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end Understand how to use different modeling and feature engineering approaches fluently Examine the options for avoiding common pitfalls of modeling, such as overfitting Learn practical methods to prepare your data for modeling Tune models for optimal performance Use good statistical practices to compare, evaluate, and choose among models
Author: Cyrille Rossant
Publisher: Packt Publishing Ltd
ISBN: 1785881930
Category : Computers
Languages : en
Pages : 548
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Book Description
Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Book Description Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. What you will learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory Who this book is for This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
