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Podcasts
The Elastic Stack helps you work with massive volumes of data to power use cases in the search, observability, and security solution areas.This three-part book starts with an introduction to the Elastic Stack with high-level commentary on the solutions the stack can be leveraged for. The second section focuses on each core component, giving you a detailed understanding of the component and the role it plays. You’ll start by working with Elasticsearch to ingest, search, analyze, and store data for your use cases. Next, you’ll look at Logstash, Beats, and Elastic Agent as components that can collect, transform, and load data. Later chapters help you use Kibana as an interface to consume Elastic solutions and interact with data on Elasticsearch. The last section explores the three main use cases offered on top of the Elastic Stack. You’ll start with a full-text search and look at real-world outcomes powered by search capabilities. Furthermore, you’ll learn how the stack can be used to monitor and observe large and complex IT environments. Finally, you’ll understand how to detect, prevent, and respond to security threats across your environment. The book ends by highlighting architecture best practices for successful Elastic Stack deployments.By the end of this book, you’ll be able to implement the Elastic Stack and derive value from it.
The future of IoT has the potential to be limitless. Wouldn’t it be great if you could add it to your own technological stacks? But where to start? With the basics, of course.In this book, you will start by learning about the most popular hardware and communication protocol, Raspberry Pi and MQTT. You will see how to use them together by setting up your own MQTT server on Raspberry Pi and understand how it works.This book explores MQTT in detail, including the clients and devices that you can connect to your server. You will discover two very popular IoT development boards among project developers: the ESP8266 and ESP32 development boards. Then, you will learn how to build interactive dashboards on your Pi and monitor your client devices. The book also shows you how to build a dashboard using another popular software – Node-RED. You will be able to put your skills to the test by creating two full-scale projects. That’s not all: you will also learn how to host your own MQTT server on a virtual cloud service. Finally, you will be guided on how to move forward from here, what technologies to learn, and some project recommendations to polish or test your knowledge.By the end of this book, you will be able to build meaningful projects using Raspberry Pi and MQTT and create dashboards for your projects on Node-RED.
AI Explained. Uncovering the Reality, Risks, and Rewards of Artificial Intelligence
This book leads readers on a comprehensive journey through artificial intelligence, beginning with an introduction to its foundational concepts. Early on, readers are guided through what AI is and why it’s becoming a transformative force in today’s world. They’ll then explore the technical processes behind AI creation, learning how data and algorithms power intelligent systems, making complex technology accessible and understandable.Further on, the book delves into practical applications and ethical considerations. Readers discover the positive ways AI is improving our lives, from breakthroughs in healthcare to innovations in everyday industries. Following this, it presents a balanced view of AI’s potential risks, discussing the ethical concerns and societal challenges that arise with misuse, encouraging thoughtful reflection on AI’s impact.Towards the end, the book tackles critical future challenges and solutions. It discusses the threat of rogue AI behaviors and highlights strategies to prevent AI from acting unpredictably. The final section offers an optimistic outlook on the responsible development of AI, encouraging readers to envision a future where AI can drive positive change. By journey’s end, readers will feel equipped with a nuanced understanding of AI, its real-world significance, and its ethical implications.
Angelika Klidas, Kevin Hanegan
Data is more than a mere commodity in our digital world. It is the ebb and flow of our modern existence. Individuals, teams, and enterprises working with data can unlock a new realm of possibilities. And the resultant agility, growth, and inevitable success have one origin—data literacy.This comprehensive guide is written by two data literacy pioneers, each with a thorough footprint within the data and analytics commercial world and lectures at top universities in the US and the Netherlands. Complete with best practices, practical models, and real-world examples, Data Literacy in Practice will help you start making your data work for you by building your understanding of data literacy basics and accelerating your journey to independently uncovering insights.You’ll learn the four-pillar model that underpins all data and analytics and explore concepts such as measuring data quality, setting up a pragmatic data management environment, choosing the right graphs for your readers, and questioning your insights.By the end of the book, you'll be equipped with a combination of skills and mindset as well as with tools and frameworks that will allow you to find insights and meaning within your data for data-informed decision making.
Marius Bancila, Raffaele Rialdi, Ankit Sharma, Dino Esposito
The C# programming language is often developers’ primary choice for creating a wide range of applications for desktop, cloud, and mobile. In nearly two decades of its existence, C# has evolved from a general-purpose, object-oriented language to a multi-paradigm language with impressive features.This book will take you through C# from the ground up in a step-by-step manner. You'll start with the building blocks of C#, which include basic data types, variables, strings, arrays, operators, control statements, and loops. Once comfortable with the basics, you'll then progress to learning object-oriented programming concepts such as classes and structures, objects, interfaces, and abstraction. Generics, functional programming, dynamic, and asynchronous programming are covered in detail. This book also takes you through regular expressions, reflection, memory management, pattern matching, exceptions, and many other advanced topics. As you advance, you'll explore the .NET Core 3 framework and learn how to use the dotnet command-line interface (CLI), consume NuGet packages, develop for Linux, and migrate apps built with .NET Framework. Finally, you'll understand how to run unit tests with the Microsoft unit testing frameworks available in Visual Studio.By the end of this book, you’ll be well-versed with the essentials of the C# language and be ready to start creating apps with it.
When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one. You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this book, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.
Python Essentials for AWS Cloud Developers. Run and deploy cloud-based Python applications using AWS
AWS provides a vast variety of services for implementing Python applications, which can pose a challenge for those without an AWS background. This book addresses one of the more predominant problems of choosing the right service and stepping into the implementation of exciting Python apps using AWS.The book begins by showing you how to install Python and create an AWS account, before helping you explore AWS Lambda, EC2, Elastic Beanstalk, and S3 for Python programming. You'll then gain hands-on experience in using these services to build the Python application. As you advance, you'll discover how to debug Python apps using PyCharm, and then start deploying the Python applications on Elastic Beanstalk. You’ll also learn how to monitor Python applications using the CloudWatch service, along with creating and publishing APIs on AWS to access the Python application. The concluding chapters will help you get to grips with storing unstructured and semi-structured data using NoSQL and DynamoDB, as well as advance your knowledge using the Glue serverless data integration service in AWS.By the end of this Python book, you’ll be able to take your application development skills up a notch with AWS services and advance in your career.