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Implementing Service Level Objectives
Implementing Service Level Objectives

Although service-level objectives (SLOs) continue to grow in importance, there's a distinct lack of information about how to implement them. Practical advice that does exist usually assumes that your team already has the infrastructure, tooling, and culture in place. In this book, recognized SLO expert Alex Hidalgo explains how to build an SLO culture from the ground up. Ideal as a primer and daily reference for anyone creating both the culture and tooling necessary for SLO-based approaches to reliability, this guide provides detailed analysis of advanced SLO and service-level indicator (SLI) techniques. Armed with mathematical models and statistical knowledge to help you get the most out of an SLO-based approach, you'll learn how to build systems capable of measuring meaningful SLIs with buy-in across all departments of your organization. ...
Articulating Design Decisions, 2nd Edition
Articulating Design Decisions, 2nd Edition

Talking to people about your designs might seem like a basic skill, but it can be difficult to do well. In many cases, how you communicate with stakeholders, clients, and other nondesigners may be more important than the designs themselves. Because if you can't get their support, your work will never see the light of day - no matter how good it is. This practical guide focuses on principles, tactics, and actionable methods for presenting your designs. Whether you design apps, websites, or products, you'll learn how to get support from people who have influence over the project with the goal of creating the best user experience. ...
Deep Learning for Coders with fastai and PyTorch
Deep Learning for Coders with fastai and PyTorch

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. ...
Practical Apache Lucene 8
Practical Apache Lucene 8

Gain a thorough knowledge of Lucene's capabilities and use it to develop your own search applications. This book explores the Java-based, high-performance text search engine library used to build search capabilities in your applications. Starting with the basics of Lucene and searching, you will learn about the types of queries used in it and also take a look at scoring models. Applying this basic knowledge, you will develop a hello world app using basic Lucene queries and explore functions like scoring and document level boosting. Along the way you will also uncover the concepts of partial searching and matching in Lucene and then learn how to integrate geographical information (geospatial data) in Lucene using spatial queries and n-dimensional indexing. This will prepare you to build a location-aware search engine with a representative data set that allows location constraints to be specified during a search. You'll also develop a text classifier using Lucene and Apache Mahout, ...
Tiny Python Projects
Tiny Python Projects

A long journey is really a lot of little steps. The same is true when you're learning Python, so you may as well have some fun along the way! Written in a lighthearted style with entertaining exercises that build powerful skills, Tiny Python Projects takes you from amateur to Pythonista as you create 22 bitesize programs. Each tiny project teaches you a new programming concept, from the basics of lists and strings right through to regular expressions and randomness. Along the way you'll also discover how testing can make you a better programmer in any language. Who says learning to program has to be boring? The 21 activities in this book teach Python fundamentals through puzzles and games. Not only will you be entertained with every exercise, but you'll learn about text manipulation, basic algorithms, and lists and dictionaries as you go. It's the ideal way for any Python newbie to gain confidence and experience. The projects are tiny, but the rewards are big: each chapter in Tin ...
Deep Learning with PyTorch
Deep Learning with PyTorch

Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you - and your deep learning skills - become more sophisticated. Deep Learning with PyTorch will make that journey engaging and fun. Although many deep learning tools use Python, the PyTorch library is truly Pythonic. Instantly familiar to anyone who knows PyData tools like NumPy and scikit-learn, PyTorch simplifies deep learning without sacrificing advanced features. It's excellent for building quick models, and it scales smoothly from laptop to enterprise. Because companies like Apple, Facebook, and JPMorgan Chase rely on PyTorch, it's a great skill to have as you expand your career options. It's easy to get started with PyTorch. It minimizes cognitive overhead w ...
AI as a Service
AI as a Service

Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development - and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you'll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That ...
Write Great Code: Volume 1, 2nd Edition
Write Great Code: Volume 1, 2nd Edition

This, the first volume in Randall Hyde's Write Great Code series, dives into machine organization without the extra overhead of learning assembly language programming. Written for high-level language programmers, Understanding the Machine fills in the low-level details of machine organization that are often left out of computer science and engineering courses. Learn: How the machine represents numbers, strings, and high-level data structures, so you'll know the inherent cost of using them; How to organize your data, so the machine can access it efficiently; How the CPU operates, so you can write code that works the way the machine does; How I/O devices operate, so you can maximize your application's performance when accessing those devices; How to best use the memory hierarchy to produce the fastest possible programs. Great code is efficient code. But before you can write truly efficient code, you must understand how computer systems execute programs and how abstractions in prog ...
Write Great Code: Volume 2, 2nd Edition
Write Great Code: Volume 2, 2nd Edition

Today's programming languages offer productivity and portability, but also make it easy to write sloppy code that isn't optimized for a compiler. Thinking Low-Level, Writing High-Level will teach you to craft source code that results in good machine code once it's run through a compiler. You'll learn: How to analyze the output of a compiler to verify that your code generates good machine code; The types of machine code statements that compilers generate for common control structures, so you can choose the best statements when writing HLL code; Enough assembly language to read compiler output; How compilers convert various constant and variable objects into machine data. With an understanding of how compilers work, you'll be able to write source code that they can translate into elegant machine code. ...
Practical Vulnerability Management
Practical Vulnerability Management

Bugs: they're everywhere. Software, firmware, hardware - they all have them. Bugs even live in the cloud. And when one of these bugs is leveraged to wreak havoc or steal sensitive information, a company's prized technology assets suddenly become serious liabilities. Fortunately, exploitable security weaknesses are entirely preventable; you just have to find them before the bad guys do. Practical Vulnerability Management will help you achieve this goal on a budget, with a proactive process for detecting bugs and squashing the threat they pose. The book starts by introducing the practice of vulnerability management, its tools and components, and detailing the ways it improves an enterprise's overall security posture. Then it's time to get your hands dirty! As the content shifts from conceptual to practical, you're guided through creating a vulnerability-management system from the ground up, using open-source software. Along the way, you'll learn how to: Generate accurate and usa ...
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