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Dive Into Algorithms
Dive Into Algorithms

Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math, you'll explore standard computer science algorithms for searching, sorting, and optimization; human-based algorithms that help us determine how to catch a baseball or eat the right amount at a buffet; and advanced algorithms like ones used in machine learning and artificial intelligence. You'll even explore how ancient Egyptians and Russian peasants used algorithms to multiply numbers, how the ancient Greeks used them to find greatest common divisors, and how Japanese scholars in the age of samurai designed algorithms capable of generating magic squares. You'll explore algorithms that are useful in pure mathematics and learn how mathematical ideas can improve algorithms. You'll learn about an algorithm for generating continued fractions, one for quick calculations of square roots, and anot ...
Algorithmic Thinking
Algorithmic Thinking

Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: - The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book; - Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations; - The union-find data structure to answer questions about c ...
How Computers Really Work
How Computers Really Work

How Computers Really Work is a hands-on guide to the computing ecosystem: everything from circuits to memory and clock signals, machine code, programming languages, operating systems, and the internet. But you won't just read about these concepts, you'll test your knowledge with exercises, and practice what you learn with 41 optional hands-on projects. Build digital circuits, craft a guessing game, convert decimal numbers to binary, examine virtual memory usage, run your own web server, and more. Explore concepts like how to: - Think like a software engineer as you use data to describe a real world concept; - Use Ohm's and Kirchhoff's laws to analyze an electrical circuit; - Think like a computer as you practice binary addition and execute a program in your mind, step-by-step. The book's projects will have you translate your learning into action, as you: - Learn how to use a multimeter to measure resistance, current, and voltage; - Build a half adder to see how logical op ...
Beyond the Basic Stuff with Python
Beyond the Basic Stuff with Python

You've completed a basic Python programming tutorial or finished Al Sweigart's best selling Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program - not just in Python but in any language. You'll learn: - Coding style, and how to use Python's Black aut ...
Practical Deep Learning
Practical Deep Learning

If you've been curious about machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: - How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines; - How neural networks work and how they're trained; - How to use convolutional neural network ...
Programming DSLs in Kotlin
Programming DSLs in Kotlin

Creating your own domain-specific languages (DSLs) is both challenging and exhilarating. DSLs give users a way to interact with your applications more effectively, and Kotlin is a fantastic language to serve as a host for internal DSLs, because it greatly reduces the pain and effort of design and development. But implementing DSLs on top of Kotlin requires understanding the key strengths of the language and knowing how to apply them appropriately. Learn to avoid the pitfalls and leverage the language while creating your own elegant, fluent, concise, and robust DSLs using Kotlin. Internal DSLs remove the burdens of implementing a full blown language compiler. The host language quickly becomes your ally to creating DSLs, but the syntax you can choose for your DSLs is limited to what the host language allows. You can work around the limitations by tactfully bending the rules and exploiting the language capabilities. Learn the power of Kotlin and ways to design with it, in the context o ...
Design and Build Great Web APIs
Design and Build Great Web APIs

APIs are transforming the business world at an increasing pace. Gain the essential skills needed to quickly design, build, and deploy quality web APIs that are robust, reliable, and resilient. Go from initial design through prototyping and implementation to deployment of mission-critical APIs for your organization. Test, secure, and deploy your API with confidence and avoid the "release into production" panic. Tackle just about any API challenge with more than a dozen open-source utilities and common programming patterns you can apply right away. Good API design means starting with the API-first principle - understanding who is using the API and what they want to do with it - and applying basic design skills to match customers' needs while solving business-critical problems. Use the Sketch-Design-Build method to create reliable and scalable web APIs quickly and easily without a lot of risk to the day-to-day business operations. Create clear sequence diagrams, accurate specifications ...
Understanding the DOM
Understanding the DOM

JavaScript is the de facto programming language of the web, but the language itself does not include any built-in method for working with input/output (I/O), such as graphics display and sound. Instead, the web browser provides an API for accessing the HTML document in a tree structure known as the Document Object Model (DOM). The combination of JavaScript and the DOM is what allows us to create interactive, dynamic websites. Many modern frameworks, such as React, Vue, and Svelte abstract away much of the DOM from the developer, but frameworks also use the DOM under the hood. The JavaScript library jQuery was also created to make working with the DOM easier, but the modern development practice is to work with the DOM directly. In order to be a proficient web developer, having a deep understanding of what the DOM is and how to work with it is essential. The goal of this book is to provide a base understanding of the DOM, as well as explore examples of the most common and useful metho ...
Mastering Python for Bioinformatics
Mastering Python for Bioinformatics

Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained, usually by students and researchers who've never learned basic programming skills. This practical guide shows postdoc bioinformatics professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools including linters, formatters, type checkers, and tests to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming. - Create command-line Python programs to document and validate parameters - Write tests to verify refactor p ...
Mastering Shiny
Mastering Shiny

Master the Shiny web framework - and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep int ...
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