Mastering Python for BioinformaticsLife 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 ...
Clever AlgorithmsThis book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language. ...
Practical Machine Learning for Computer VisionThis practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.
Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.
You'll learn how to: Design ML architecture for computer vision tasks; Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropri ...
SQL Pocket Guide, 4th EditionIf you use SQL in your day-to-day work as a data analyst, data scientist, or data engineer, this popular pocket guide is your ideal on-the-job reference. You'll find many examples that address the language's complexities, along with key aspects of SQL used in Microsoft SQL Server, MySQL, Oracle Database, PostgreSQL, and SQLite.
In this updated edition, author Alice Zhao describes how these database management systems implement SQL syntax for both querying and making changes to a database. You'll find details on data types and conversions, regular expression syntax, window functions, pivoting and unpivoting, and more.
Quickly look up how to perform specific tasks using SQL; Apply the book's syntax examples to your own queries; Update SQL queries to work in five different database management systems; Connect Python and R to a relational database; Look up frequently asked SQL questions in the "How Do I?" chapter. ...
Financial Theory with PythonNowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.
Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.
Draw upon mathematics to learn the foundations of financial theory and Python programming; Learn about financial theory, financial data modeling, and the use of Python for computational finance; Leverage simple economic models to better understand basic notions of finance and Python programming co ...
C# CookbookEven if you're familiar with C# syntax, knowing how to combine various language features is a critical skill when you're building applications. This cookbook is packed full of recipes to help you solve issues for C# programming tasks you're likely to encounter. You'll learn tried-and-true techniques to help you achieve greater productivity and improve the quality of your code.
Author and independent consultant Joe Mayo shares some of the most important practices you'll need to be successful as a C# developer. Each section of this cookbook describes some useful facet of the C# programming language. These recipes - the result of many years of experience-are proven concepts for solving real-world problems with C#.
Recipes in this book will help you: Set up your project, manage object lifetime, and establish patterns; Improve code quality through maintainability, error prevention, and correct syntax; Use LINQ to Objects for in-memory data manipulation and querying; Understand the dif ...
Cloud Design PatternsCloud applications have a unique set of characteristics. They run on commodity hardware, provide services to untrusted users, and deal with unpredictable workloads. These factors impose a range of problems that you, as a designer or developer, need to resolve. Your applications must be resilient so that they can recover from failures, secure to protect services from malicious attacks, and elastic in order to respond to an ever changing workload. This guide demonstrates design patterns that can help you to solve the problems you might encounter in many different areas of cloud application development. Each pattern discusses design considerations, and explains how you can implement it using the features of Windows Azure. The patterns are grouped into categories: availability, data management, design and implementation, messaging, performance and scalability, resilience, management and monitoring, and security. You will also see more general guidance related to these areas of concern. It ...
MLOps Engineering at ScaleMLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You'll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities.
A production-ready machine learning system includes efficient data pipelines, integrated monitoring, and means to scale up and down based on demand. Using cloud-based services to implement ML infrastructure reduces development time and lowers hosting costs. Serverless MLOps eliminates the need to build and maintain custom infrastructure, so you can concentrate on your data, models, and algorithms.
MLOps Engineering at Scale teaches you how to implement efficient machine learning systems usi ...
Kafka in ActionKafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you'll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics.
Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications.
Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you'll explore the most common use cases such as logging and managing streaming data. When you're done, you'll be ready to handle both basic developer- and admi ...
Microsoft Visual C# Step by Step, 10th EditionExpand your expertiseand teach yourself the fundamentals of programming the latest version of Visual C# with Visual Studio 2022. This book provides software developers all the guidance, exercises, and code needed to start building responsive, scalable, cloud-connected applications that can run almost anywhere.
Discover how to: Quickly start creating Visual C# code and projects with Visual Studio; Work with variables, operators, expressions, methods, and program flow; Build more robust apps with error, exception, and resource management; Spot problems fast with the integrated Visual Studio 2022 debugger; Master new default interface methods, static local functions, async disposable types, and other enhancements; Make the most of the C# object model, and create functional data structures; Leverage advanced properties, indexers, generics, and collection classes; Create Windows 11 apps that share data, collaborate, and use cloud services; Use lightweight records to build immutable ref ...