The Foundational Hands-On Skills You Need to Dive into Data Science
âFreeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.â âFrom the foreword by Jared Lander, series editor
âFreeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.â
âFrom the foreword by Jared Lander, series editor
Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.
Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns youâve uncovered. Step by step, youâll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.
Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everythingâs focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to
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The award-winning and highly influential Software Architecture in Practice, Third Edition, has been substantially revised to reflect the latest developments in the field. In a real-world setting, the book once again introduces the concepts and best practices of software architectureâhow a software system is structured and how that systemâs elements are meant to interact. Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organizationâs business strategy.
The authors have structured this edition around the concept of architecture influence cycles. Each cycle shows how architecture influences, and is influenced by, a particular context in which architecture plays a critical role. Contexts include technical environment, the life cycle of a project, an organizationâs business profile, and the architectâs professional practices. The authors also have greatly expanded their treatment of quality attributes, which remain central to their architecture philosophyâwith an entire chapter devoted to each attributeâand broadened their treatment of architectural patterns.
If you design, develop, or manage large software systems (or plan to do so), you will find this book to be a valuable resource for getting up to speed on the state of the art.
Totally new material coversÂ Â
Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs.
The bookÂ contains 33 different styles for writing the term frequency task. The styles are grouped into nine categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, and interactivity. The author verbalizes the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.
Ace technical interviews with smart preparation
Programming Interviews Exposed is the programmerâs ideal first choice for technical interview preparation. Updated to reflect changing techniques and trends, this new fourth edition provides insider guidance on the unique interview process that today's programmers face. Online coding contests are being used to screen candidate pools of thousands, take-home projects have become commonplace, and employers are even evaluating a candidate's public code repositories at GitHubâand with competition becoming increasingly fierce, programmers need to shape themselves into the ideal candidate well in advance of the interview. This book doesn't just give you a collection of questions and answers, it walks you through the process of coming up with the solution so you learn the skills and techniques to shine on whatever problems youâre given.
This edition combines a thoroughly revised basis in classic questions involving fundamental data structures and algorithms with problems and step-by-step procedures for new topics including probability, data science, statistics, and machine learning which will help you fully prepare for whatever comes your way.
Technical jobs require the skillset, but you wonât get hired unless you are able to effectively and efficiently demonstrate that skillset under pressure, in competition with hundreds of others with the same background. Programming Interviews Exposed teaches you the interview skills you need to stand out as the best applicant to help you get the job you want.
A comprehensive introduction to type systems and programming languages.
A type system is a syntactic method for automatically checking the absence of certain erroneous behaviors by classifying program phrases according to the kinds of values they compute. The study of type systemsâand of programming languages from a type-theoretic perspectiveâhas important applications in software engineering, language design, high-performance compilers, and security.
This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.
The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.
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