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. Found inside â Page 1But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? Found insideThis book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges. This book starts off with a refresher on installing and running Julia on different platforms. Found insideTackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques About This Book Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and ... Found insideThis beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems. This Learning Path is your step-by-step guide to learn the high-level and high-performance Julia language and build simple-to-advanced applications with it using modern tools. Found inside â Page iWho This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Found inside â Page 4Python. vs. R,. Julia,. and. Others. If you are new to programming, ... If machine learning is relevant for you, several of the most powerful machine ... Found insideThis hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Found inside â Page iPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Found insideThey provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications. This book will be your solution-based guide as it will take you through different programming aspects with Julia. By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs. Found inside â Page 37Table 1-13 summarizes Python set operations, Listing 1-29 shows example code for creating ... 'r', 'Julia']) removing all items/ elements from a set clear() ... This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo Balbaert Julia Programming Projects by Adrian Salceanu What you will learn Create your own types to extend the built-in ... The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students. What you will learn Leverage Julia's strengths, its top packages, and main IDE options Analyze and manipulate datasets using Julia and DataFrames Write complex code while building real-life Julia applications Develop and run a web app using ... 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. It has C-like execution speed with excellent applications in multi-core, GPU, and cloud computing. Julia Programming Projects explains all this with the support of Julia v1.0. Found insideHe is a deep learning early adopter and is currently working on a large-scale cloud-based ... He enjoys programming in Scala, Python, R, Java, and Julia. 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. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications. Found inside â Page 1Each language in Seven More Languages in Seven Weeks will take you on a step-by-step journey through the most important paradigms of our time. You'll learn seven exciting languages: Lua, Factor, Elixir, Elm, Julia, MiniKanren, and Idris. Found insideThis book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Found insideWhile some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you. Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn ... Found insideLearn to build powerful machine learning models quickly and deploy large-scale predictive applications About This Book Design, engineer and deploy scalable machine learning solutions with the power of Python Take command of Hadoop and Spark ... Found insideA quick guide to start writing your own fun and useful Julia appsâno prior experience required! This engaging guide shows, step by step, how to build custom programs using Julia, the open-source, intuitive scripting language. Found inside â Page iThe best algorithms are undergirded by beautiful mathematics. This text cuts across discipline boundaries to highlight some of the most famous and successful algorithms. With a foreword written by Joe Armstrong, this handbook offers an extensive tutorial for creating a state of the art Topology and Weight Evolving Artificial Neural Network (TWEANN) platform. "This video provides a brief introduction to using Julia for data science. The presenter of this video, Zacharias Voulgaris, is author of these two books which are both available on Safari: 'Data Scientist' and 'Julia for Data Science'. Found insideYour Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. This book is neither a textbook in numerical methods, a comprehensive introductory book to Julia programming, a textbook on numerical optimization, a complete manual of optimization solvers, nor an introductory book to computational science ... If youâre an experienced programmer interested in crunching data, this book will get you started with machine learningâa toolkit of algorithms that enables computers to train themselves to automate useful tasks. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. Found insideThe book then extends Râs data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. Found inside â Page 1About the Book His book, Hello Swift! iOS app programming for kids and other beginners, teaches you how to write apps for iPhones and iOS devices step by step, starting with your first line of Swift code. Found insideThis book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. "Julia walks like Python and runs like C". This phrase explains why Julia is fast growing as the most favoured option for data analytics and numerical computation. Found insideBy 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. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. The field of AI is vast, and can be overwhelming for the newcomer to approach. This book will arm you with a solid understanding of the field, plus inspire you to explore further. Found insidePython Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. In this book, you will learn how to build interactive dashboards in a Jupyter notebook. Found insideNow, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. 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 ... This anthology of essays from the inventor of literate programming includes Knuth's early papers on related topics such as structured programming, as well as the Computer Journal article that launched literate programming itself. Found insideUnleash the power of Julia for your machine learning tasks. We reveal why Julia is chosen for more and more data science and machine learning projects, including Juliaâs ability to run algorithms at lightning speed. Introduction to using Julia, the open-source, intuitive scripting language with.... With it using modern tools object types, this book starts off with refresher! 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