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Podcasty
Securing connected industries and autonomous systems is of primary concern to the Industrial Internet of Things (IIoT) community. Unlike cybersecurity, cyber-physical security directly ties to system reliability as well as human and environmental safety.This hands-on guide begins by establishing the foundational concepts of IIoT security with the help of real-world case studies, threat models, and reference architectures. You’ll work with practical tools to design risk-based security controls for industrial use cases and gain practical knowledge of multi-layered defense techniques, including identity and access management (IAM), endpoint security, and communication infrastructure. You’ll also understand how to secure IIoT lifecycle processes, standardization, and governance. In the concluding chapters, you’ll explore the design and implementation of resilient connected systems with emerging technologies such as blockchain, artificial intelligence, and machine learning.By the end of this book, you’ll be equipped with the all the knowledge required to design industry-standard IoT systems confidently.
Chandra Sekhar Nayak, Rivu Chakraborty
Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory.Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally.By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems.
Alexander Combs, Michael Roman
Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects.The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks.By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects.
Aaron Ploetz, Devram Kandhare, Sudarshan Kadambi, Xun (Brian) Wu
This is the golden age of open source NoSQL databases. With enterprises having to work with large amounts of unstructured data and moving away from expensive monolithic architecture, the adoption of NoSQL databases is rapidly increasing. Being familiar with the popular NoSQL databases and knowing how to use them is a must for budding DBAs and developers.This book introduces you to the different types of NoSQL databases and gets you started with seven of the most popular NoSQL databases used by enterprises today. We start off with a brief overview of what NoSQL databases are, followed by an explanation of why and when to use them. The book then covers the seven most popular databases in each of these categories: MongoDB, Amazon DynamoDB, Redis, HBase, Cassandra, In?uxDB, and Neo4j. The book doesn't go into too much detail about each database but teachesyou enough to get started with them.By the end of this book, you will have a thorough understanding of the different NoSQL databases and their functionalities, empowering you to select and use the rightdatabase according to your needs.
Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective.You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data.By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.
Alena Traukina, Jayant Thomas, Prashant Tyagi, Veera Kishore Reddipalli
The Industrial Internet refers to the integration of complex physical machines with networked sensors and software. The growth in the number of sensors used in industrial machinery has led to an exponential increase in data being captured for predictive analytics.Industrial Internet Application Development is a practical guide for developers who want to create applications that leverage the full capabilities of IIoT. You will get started by learning how to develop your first IIoT application and understanding its deployment and security. Once you’re familiar with what IIoT is, you will move on to exploring Edge Development along with the analytics aspect of the IIoT stack. In later chapters, you’ll get to grips with the deployment of IIoT applications on the Predix platform. As you cover these concepts, you’ll be able to identify key elements of the development framework and understand their importance while considering architecture and design for IIoT applications.By the end of this book, you will have the skills you need to deploy IIoT applications on the Predix platform and incorporate best practices for developing fault-tolerant and reliable IIoT systems.
WordPress is the most used CMS in the world and is the ideal way to share your knowledge with a large audience or build a profitable business. Getting started with WordPress development has often been a challenge for novice developers, and this book will help you find your way.This book explains the components used in WordPress development, when and where to use them, and why you should be using each component in specific scenarios. You begin by learning the basic development setup and coding standards of WordPress. Then you move into the most important aspects of the theme and plugin development process. Here you will also learn how themes and plugins fit into the website while learning about a range of techniques for extending themes and plugins.With the basics covered, we explore many of the APIs provided by WordPress and how we can leverage them to build rapid solutions. Next, we move on to look at the techniques for capturing, processing, and displaying user data when integrating third-party components into the site design.Finally, you will learn how to test and deploy your work with secure and maintainable code, while providing the best performance for end users.
If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems.You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.