Clojure In Small PiecesRich Hickey invented Clojure. This is a fork of the project to experiment with literate programming as a development and documentation technology.
Clojure is a break with the past traditions of Lisp. This literate fork is a break with the past traditions of code development. As such it is intended as an experiment, not a replacement or competition with the official version of Clojure.
Most programmers are still locked into the idea of making a program out of a large pile of tiny files containing pieces of programs. They do not realize that this organization was forced by the fact that machines like the PDP 11 only had 8k of memory and a limit of 4k buffers in the editor. Thus there was a lot of machinery built up, such as overlay linkers, to try to reconstruct the whole program.
The time has come to move into a more rational means of creating and maintaining programs. Knuth suggested we write programs like we write literature, with the idea that we are trying to communicate th ...
Azure Maps Using Blazor SuccinctlyMicrosoft Azure Maps is part of Microsoft Azure Cloud Services and provides a wide range of powerful geospatial capabilities and a rich set of REST APIs. It has SDKs for both web and mobile applications. In Azure Maps Using Blazor Succinctly, learn how you can create sophisticated applications with Azure Maps and Syncfusion controls in Blazor. Michael Washington will introduce you to the capabilities of Azure Maps and then take you through the steps of building a Blazor store application featuring it. ...
Software Development with GoGain insights into the different challenges that can be solved using Go, with a focus on containers, Linux, security, networking, user interfaces and other relevant cloud based topics. This book reviews the necessary tools to create container-based cloud solutions with Go, a programming language that was born out of the need to address scalable, high availability cloud computing architecture needs inside Google.
Go, also known as Golang, has been adopted across different industries and products with many popular Open Source projects that power cloud computing technologies such as Docker and Kubernetes being written with Go. As the complexity of cloud technology increases, so does the need for people to understand how things work under-the-hood and to fix them when they're broken. ...
Simple and Efficient Programming with C#, 2nd EditionApply skills and approaches to your programming to build a real-world application in C# 11 using the latest editions of Visual Studio, C#, and Microsoft .NET.
This revised edition is updated with C#11 and places more emphasis on the newly introduced top-level statements. Additionally, you will find useful techniques and an explanation of the differences between writing code in two different styles. It also covers the new templates introduced in .NET 6, along with usage of .NET 7 in Windows 10 to write code and generate output.
Each chapter opens with an introduction and original application written in C# 11 so that you can jump right into coding. From there, you are guided through an expected output and taught best practices along the way. Author Vaskaran Sarcar emphasizes extending and maintaining the same program and he demonstrates examples for different scenarios to make your program more efficient and effective.
This book is divided into five parts. The first part starts ...
Numerical Methods Using KotlinThis in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started.
In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems.
After reading this book, you'll come away with the knowledge to create your own numerical models and algori ...
Foundations of ARM64 Linux Debugging, Disassembling, and ReversingGain a solid understanding of how Linux C and C++ compilers generate binary code. This book explains the reversing and binary analysis of ARM64 architecture now used by major Linux cloud providers and covers topics ranging from writing programs in assembly language, live debugging, and static binary analysis of compiled C and C++ code. It is ideal for those working with embedded devices, including mobile phones and tablets.
Using the latest version of Red Hat, you'll look closely at the foundations of diagnostics of core memory dumps, live and postmortem debugging of Linux applications, services, and systems. You'll also work with the GDB debugger and use it for disassembly and reversing. This book uses practical step-by-step exercises of increasing complexity with explanations and many diagrams, including some necessary background topics. In addition, you will be able to analyze such code confidently, understand stack memory usage, and reconstruct original C/C++ code.
And as yo ...
Productionizing AIThis book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app.
From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you'll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You'll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions.
The b ...
Beginning Spring DataUse the popular Spring Data project for data access and persistence using various Java-based APIs such as JDBC, JPA, MongoDB, and more.
This book shows how to easily incorporate data persistence and accessibility into your microservices, cloud-native applications, and monolithic enterprise applications. It also teaches you how to perform unit and performance testing of a component that accesses a database. And it walks you through an example of each type of SQL and NoSQL database covered.
After reading this book, you'll be able to create an application that interacts with one or multiple types of databases, and conduct unit and performance testing to analyze possible problems. ...
Advanced Data Analytics Using Python, 2nd EditionUnderstand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment.
Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning.
Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Statistical Learning and Sequential PredictionThis free book will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability and statistics, game theory, algorithms, and optimization. It is this blend of ideas that makes the subject interesting for us, and we hope to convey the excitement. We shall try to make the course as self-contained as possible, and pointers to additional readings will be provided whenever necessary. Our target audience is graduate students with a solid background in probability and linear algebra. ...