Books: 12

Haskell

CoverTitleYear
Safety-Driven Web Development
This fast-moving guide introduces web application development with Haskell and Yesod, a potent language/framework combination that supports high-performing applications that are modular, type-safe, and concise. Fully updated for Yesod 1.4, this second edition shows you how Yesod handles widgets, forms, more » persistence, and RESTful content. Author Michael Snoyman also introduces various Haskell tools to supplement your basic knowledge of the language. By the time you finish this book, you'll create a production-quality web application with Yesod's ready-to-use scaffolding. You'll also examine several real-world examples, including a blog, a wiki, a JSON web service, and a Sphinx search server. « less
2015
Analyze, manipulate, and process datasets of varying sizes efficiently using Haskell
***** About This Book ***** * Create portable databases using SQLite3 and use these databases to quickly pull large amounts of data into your Haskell programs. * Visualize data using EasyPlot and create publication-ready charts * An easy-to-follow guide to analyze real-world data using the most more » commonly used statistical techniques ***** Who This Book Is For ***** If you are a developer, analyst, or data scientist who wants to learn data analysis methods using Haskell and its libraries, then this book is for you. Prior experience with Haskell and a basic knowledge of data science will be beneficial. ***** What You Will Learn ***** * Learn the essential tools of Haskell needed to handle large data * Migrate your data to a database and learn to interact with your data quickly * Clean data with the power of Regular Expressions * Plot data with the Gnuplot tool and the EasyPlot library * Formulate a hypothesis test to evaluate the significance of your data * Evaluate the variance between columns of data using a correlation statistic and perform regression analysis ***** In Detail ***** Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of code that will be used to solve a problem for that chapter. The book starts with creating databases out of existing datasets, cleaning that data, and interacting with databases within Haskell in order to produce charts for publications. It then moves towards more theoretical concepts that are fundamental to introductory data analysis, but in a context of a real-world problem with real-world data. As you progress in the book, you will be relying on code from previous chapters in order to help create new solutions quickly. By the end of the book, you will be able to manipulate, find, and analyze large and small sets of data using your own Haskell libraries. « less
2015
A Project-Based Approach
Beginning Haskell provides a broad-based introduction to the Haskell language, its libraries and environment, and to the functional programming paradigm that is fast growing in importance in the software industry. The book takes a project-based approach to learning the language that is unified around more » the building of a web-based storefront. Excellent coverage is given to the Haskell ecosystem and supporting tools. These include the Cabal build tool for managing projects and modules, the HUnit and QuickCheck tools for software testing, the Scotty framework for developing web applications, Persistent and Esqueleto for database access, and also parallel and distributed programming libraries. « less
2014
Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes
***** About This Book ***** * A practical and concise guide to using Haskell when getting to grips with data analysis * Recipes for every stage of data analysis, from collection to visualization * In-depth examples demonstrating various tools, solutions and techniques ***** Who This Book Is For more » ***** This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed. ***** What You Will Learn ***** * Obtain and analyze raw data from various sources including text files, CSV files, databases, and websites * Implement practical tree and graph algorithms on various datasets * Apply statistical methods such as moving average and linear regression to understand patterns * Fiddle with parallel and concurrent code to speed up and simplify time-consuming algorithms * Find clusters in data using some of the most popular machine learning algorithms * Manage results by visualizing or exporting data ***** In Detail ***** This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular machine learning techniques. You will begin with how to obtain and clean data from various sources. You will then learn how to use various data structures such as trees and graphs. The meat of data analysis occurs in the topics involving statistical techniques, parallelism, concurrency, and machine learning algorithms, along with various examples of visualizing and exporting results. By the end of the book, you will be empowered with techniques to maximize your potential when using Haskell for data analysis. « less
2014
Get an in-depth analysis of financial time series from the perspective of a functional programmer Overview * Understand the foundations of financial stochastic processes * Build robust models quickly and efficiently * Tackle the complexity of parallel programming In Detail Haskell is one more » of the three most influential functional programming languages available today along with Lisp and Standard ML. When used for financial analysis, you can achieve a much-improved level of prediction and clear problem descriptions. Haskell Financial Data Modeling and Predictive Analytics is a hands-on guide that employs a mix of theory and practice. Starting with the basics of Haskell, this book walks you through the mathematics involved and how this is implemented in Haskell. The book starts with an introduction to the Haskell platform and the Glasgow Haskell Compiler (GHC). You will then learn about the basics of high frequency financial data mathematics as well as how to implement these mathematical algorithms in Haskell. You will also learn about the most popular Haskell libraries and frameworks like Attoparsec, QuickCheck, and HMatrix. You will also become familiar with database access using Yesod’s Persistence library, allowing you to keep your data organized. The book then moves on to discuss the mathematics of counting processes and autoregressive conditional duration models, which are quite common modeling tools for high frequency tick data. At the end of the book, you will also learn about the volatility prediction technique. With Haskell Financial Data Modeling and Predictive Analytics, you will learn everything you need to know about financial data modeling and predictive analytics using functional programming in Haskell. What you will learn from this book * Learn how to build a FIX protocol parser * Calibrate counting processes on real data * Estimate model parameters using the Maximum Likelihood Estimation method * Use Akaike criterion to choose the best-fit model * Learn how to perform property-based testing on a generated set of input data * Calibrate ACD models with the Kalman filter * Understand parallel programming in Haskell * Learn more about volatility prediction Approach This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner. Who this book is written for This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential. « less
2013
Techniques for Multicore and Multithreaded Programming
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language's many APIs and frameworks for writing both parallel and concurrent programs. You'll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables more » you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. « less
2013
Safety-Driven Web Development
This fast-moving guide introduces web application development with Haskell and Yesod, a potent language / framework combination that supports high-performing applications that are modular, type-safe, and concise. You'll work with several samples to explore the way Yesod handles widgets, forms, persistence, more » and RESTful content. You also get an introduction to various Haskell tools to supplement your basic knowledge of the language. By the time you finish this book, you'll create a production-quality web application with Yesod's ready-to-use scaffolding. You'll also examine several real-world examples, including a blog, a wiki, a JSON web service, and a Sphinx search server. « less
2012
Richard Bird takes a radically new approach to algorithm design, namely, design by calculation. These 30 short chapters each deal with a particular programming problem drawn from sources as diverse as games and puzzles, intriguing combinatorial tasks, and more familiar areas such as data compression more » and string matching. Each pearl starts with the statement of the problem expressed using the functional programming language Haskell, a powerful yet succinct language for capturing algorithmic ideas clearly and simply. The novel aspect of the book is that each solution is calculated from an initial formulation of the problem in Haskell by appealing to the laws of functional programming. Pearls of Functional Algorithm Design will appeal to the aspiring functional programmer, students and teachers interested in the principles of algorithm design, and anyone seeking to master the techniques of reasoning about programs in an equational style. « less
2010
A Pragmatic Guide to Learning Programming Languages
You should learn a programming language every year, as recommended by The Pragmatic Programmer. But if one per year is good, how about Seven Languages in Seven Weeks? In this book you'll get a hands-on tour of Clojure, Haskell, Io, Prolog, Scala, Erlang, and Ruby. Whether or not your favorite language more » is on that list, you'll broaden your perspective of programming by examining these languages side-by-side. You'll learn something new from each, and best of all, you'll learn how to learn a language quickly. « less
2010
This easy-to-use, fast-moving tutorial introduces you to functional programming with Haskell. You'll learn how to use Haskell in a variety of practical ways, from short scripts to large and demanding applications. Real World Haskell takes you through the basics of functional programming at a brisk pace, more » and then helps you increase your understanding of Haskell in real-world issues like I/O, performance, dealing with data, concurrency, and more as you move through each chapter. With this book, you will: * Understand the differences between procedural and functional programming * Learn the features of Haskell, and how to use it to develop useful programs * Interact with filesystems, databases, and network services * Write solid code with automated tests, code coverage, and error handling * Harness the power of multicore systems via concurrent and parallel programming You'll find plenty of hands-on exercises, along with examples of real Haskell programs that you can modify, compile, and run. Whether or not you've used a functional language before, if you want to understand why Haskell is coming into its own as a practical language in so many major organizations, Real World Haskell is the best place to start. « less
2008