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Podcasts
Desislav Andreev, Stanimir Lukanov, Milena Lazarova
Around 35 million Linux and almost 2 billion Android users rely on C++ for everything from the simplest embedded and IoT devices to cloud services, supercomputing, and space exploration. To help you produce high-quality software, two industry experts have transformed their knowledge and experience into practical examples in system programming with C++ Programming for Linux Systems.In this book, you'll explore the latest C++20 features, while working on multiple specific use cases. You’ll get familiar with the coroutines and modern approaches in concurrent and multithreaded programming. You'll also learn to reshape your thinking when analyzing system behavior in Linux (POSIX) environments. Additionally, you'll discover advanced discussions and novel solutions for complex challenges, while approaching trivial system operations with a new outlook and learning to choose the best design for your particular case.You can use this workbook as an introduction to system programming and software design in Linux or any Unix-based environment. You’ll also find it useful as a guideline or a supplement to any C++ book.By the end of this book, you’ll have gained advanced knowledge and skills for working with Linux or any Unix-based environment.
Aaron Jones, Christopher Kruger, Benjamin Johnston
Do you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.
Deep Learning from the Basics. Python and Deep Learning: Theory and Implementation
Deep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us.Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You’ll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you’ll discover backpropagation—an efficient way to calculate the gradients of weight parameters—and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays.By the end of the book, you’ll have the knowledge to apply the relevant technologies in deep learning.
Serg Masís, Aleksander Molak, Denis Rothman
Interpretable Machine Learning with Python, Second Edition, brings to light the key concepts of interpreting machine learning models by analyzing real-world data, providing you with a wide range of skills and tools to decipher the results of even the most complex models.Build your interpretability toolkit with several use cases, from flight delay prediction to waste classification to COMPAS risk assessment scores. This book is full of useful techniques, introducing them to the right use case. Learn traditional methods, such as feature importance and partial dependence plots to integrated gradients for NLP interpretations and gradient-based attribution methods, such as saliency maps.In addition to the step-by-step code, you’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability.By the end of the book, you’ll be confident in tackling interpretability challenges with black-box models using tabular, language, image, and time series data.
Eric Z. Beard, Rowan Udell, Lucas Chan
AWS is an on-demand remote computing service providing cloud infrastructure over the internet with storage, bandwidth, and customized support for APIs. This updated second edition will help you implement these services and efficiently administer your AWS environment.You will start with the AWS fundamentals and then understand how to manage multiple accounts before setting up consolidated billing. The book will assist you in setting up reliable and fast hosting for static websites, sharing data between running instances and backing up data for compliance. By understanding how to use compute service, you will also discover how to achieve quick and consistent instance provisioning. You’ll then learn to provision storage volumes and autoscale an app server. Next, you’ll explore serverless development with AWS Lambda, and gain insights into using networking and database services such as Amazon Neptune. The later chapters will focus on management tools like AWS CloudFormation, and how to secure your cloud resources and estimate costs for your infrastructure. Finally, you’ll use the AWS well-architected framework to conduct a technology baseline review self-assessment and identify critical areas for improvement in the management and operation of your cloud-based workloads.By the end of this book, you’ll have the skills to effectively administer your AWS environment.
Jerzy Kurowski, Joanna Krenz-Kurowska, Jerzy Kurowski
RESS is a new methodology in the world of web design and development. It attempts to solve the problems that accompany the RWD (responsive web design) approach to web design. RESS is still in its infancy, but it is growing at an exponential rate.RESS Essentials shows you how to make server-side applications smarter and more aware of a visitor's environment limitations (device, screen size, and browser). This allows you to create faster and more reliable websites. Through this book, you will build a solid base of knowledge on RESS-related technologies, while the step-by-step tutorials will help you to create your own RESS system.This book is an introduction to RESS alchemy and gives you an incentive to build your own RESS lab. It will give you a broad overview of the multiple techniques used to code responsive websites in responsible ways. Beginning with an overview of RWD, you will learn the steps involved in setting up RWD for client-side development. You will then learn how to scale images using client- and server-side technology. By the end of this book, you will have learned about the implementation of RESS application patterns, browser feature detection, and various RESS architectures. RESS Essentials will also teach you how to use jQuery with some RWD design patterns and how to employ REST API for RWD pages.
Unreal Engine is a powerful game development engine that provides rich functionalities to create 2D and 3D games. Developers have the opportunity to build cross-platform mobile and desktop games from scratch. This book will show you how to apply artificial intelligence (AI) techniques to your Unreal project using blueprints as your scripting language. You will start with an introduction to AI, and learn how it is applied to gaming. Then you'll jump right in and create a simple AI bot and apply basic behaviors to allow it to move randomly. As you progress, you'll find out how to implement randomness and probability traits. Using NavMesh, you will impart navigation components such as character movement, MoveTo nodes, settings, and world objects, and implement Behavior Trees. At the end of the book, you will troubleshoot any issues that might crop up while building the game.