CompTIA Data+: DAO-001 Certification Guide. Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt

Cameron Dodd

The CompTIA Data+ certification exam not only helps validate a skill set required to enter one of the fastest-growing fields in the world, but also is starting to standardize the language and concepts within the field. However, there’s a lot of conflicting information and a lack of existing resources about the topics covered in this exam, and even professionals working in data analytics may need a study guide to help them pass on their first attempt.The CompTIA Data + (DAO-001) Certification Guide will give you a solid understanding of how to prepare, analyze, and report data for better insights.You’ll get an introduction to Data+ certification exam format to begin with, and then quickly dive into preparing data. You'll learn about collecting, cleaning, and processing data along with data wrangling and manipulation. As you progress, you’ll cover data analysis topics such as types of analysis, common techniques, hypothesis techniques, and statistical analysis, before tackling data reporting, common visualizations, and data governance. All the knowledge you've gained throughout the audiobook will be tested with the mock tests that appear in the final chapters.By the end of this audiobook, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.

Learning Elixir. Unveil many hidden gems of programming functionally by taking the foundational steps with Elixir

Kenneth Ballou

Elixir, based on Erlang’s virtual machine and ecosystem, makes it easier to achieve scalability, concurrency, fault tolerance, and high availability goals that are pursued by developers using any programming language or programming paradigm. Elixir is a modern programming language that utilizes the benefits offered by Erlang VM without really incorporating the complex syntaxes of Erlang.Learning to program using Elixir will teach many things that are very beneficial to programming as a craft, even if at the end of the day, the programmer isn't using Elixir. This book will teach you concepts and principles important to any complex, scalable, and resilient application. Mostly, applications are historically difficult to reason about, but using the concepts in this book, they will become easy and enjoyable. It will teach you the functional programing ropes, to enable them to create better and more scalable applications, and you will explore how Elixir can help you achieve new programming heights. You will also glean a firm understanding of basics of OTP and the available generic, provided functionality for creating resilient complex systems. Furthermore, you will learn the basics of metaprogramming: modifying and extending Elixir to suite your needs.

Raspberry Pi Computer Architecture Essentials. Click here to enter text

Andrew K. Dennis

With the release of the Raspberry Pi 2, a new series of the popular compact computer is available for you to build cheap, exciting projects and learn about programming.In this book, we explore Raspberry Pi 2’s hardware through a number of projects in a variety of programming languages. We will start by exploring the various hardware components in detail, which will provide a base for the programming projects and guide you through setting up the tools for Assembler, C/C++, and Python. We will then learn how to write multi-threaded applications and Raspberry Pi 2’s multi-core processor. Moving on, you’ll get hands on by expanding the storage options of the Raspberry Pi beyond the SD card and interacting with the graphics hardware. Furthermore, you will be introduced to the basics of sound programming while expanding upon your knowledge of Python to build a web server. Finally, you will learn to interact with the third-party microcontrollers. From writing your first Assembly Language application to programming graphics, this title guides you through the essentials.

Google Cloud for DevOps Engineers. A practical guide to SRE and achieving Google's Professional Cloud DevOps Engineer certification

Sandeep Madamanchi

DevOps is a set of practices that help remove barriers between developers and system administrators, and is implemented by Google through site reliability engineering (SRE).With the help of this book, you'll explore the evolution of DevOps and SRE, before delving into SRE technical practices such as SLA, SLO, SLI, and error budgets that are critical to building reliable software faster and balance new feature deployment with system reliability. You'll then explore SRE cultural practices such as incident management and being on-call, and learn the building blocks to form SRE teams. The second part of the book focuses on Google Cloud services to implement DevOps via continuous integration and continuous delivery (CI/CD). You'll learn how to add source code via Cloud Source Repositories, build code to create deployment artifacts via Cloud Build, and push it to Container Registry. Moving on, you'll understand the need for container orchestration via Kubernetes, comprehend Kubernetes essentials, apply via Google Kubernetes Engine (GKE), and secure the GKE cluster. Finally, you'll explore Cloud Operations to monitor, alert, debug, trace, and profile deployed applications.By the end of this SRE book, you'll be well-versed with the key concepts necessary for gaining Professional Cloud DevOps Engineer certification with the help of mock tests.

Decoding Large Language Models. An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications

Irena Cronin

Ever wondered how large language models (LLMs) work and how they're shaping the future of artificial intelligence? Written by a renowned author and AI, AR, and data expert, Decoding Large Language Models is a combination of deep technical insights and practical use cases that not only demystifies complex AI concepts, but also guides you through the implementation and optimization of LLMs for real-world applications.You’ll learn about the structure of LLMs, how they're developed, and how to utilize them in various ways. The chapters will help you explore strategies for improving these models and testing them to ensure effective deployment. Packed with real-life examples, this book covers ethical considerations, offering a balanced perspective on their societal impact. You’ll be able to leverage and fine-tune LLMs for optimal performance with the help of detailed explanations. You’ll also master techniques for training, deploying, and scaling models to be able to overcome complex data challenges with confidence and precision. This book will prepare you for future challenges in the ever-evolving fields of AI and NLP.By the end of this book, you’ll have gained a solid understanding of the architecture, development, applications, and ethical use of LLMs and be up to date with emerging trends, such as GPT-5.

Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques

Sumit Ranjan, Dr. S. Senthamilarasu

Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving.By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries.

Big Data Forensics - Learning Hadoop Investigations. Perform forensic investigations on Hadoop clusters with cutting-edge tools and techniques

Joseph Sremack, Joe Sremack

Offensive Security Using Python. A hands-on guide to offensive tactics and threat mitigation using practical strategies

Rejah Rehim, Manindar Mohan, Grant Ongers

Offensive Security Using Python is your go-to manual for mastering the quick-paced field of offensive security. This book is packed with valuable insights, real-world examples, and hands-on activities to help you leverage Python to navigate the complicated world of web security, exploit vulnerabilities, and automate challenging security tasks.From detecting vulnerabilities to exploiting them with cutting-edge Python techniques, you’ll gain practical insights into web security, along with guidance on how to use automation to improve the accuracy and effectiveness of your security activities. You’ll also learn how to design personalized security automation tools. While offensive security is a great way to stay ahead of emerging threats, defensive security plays an equal role in protecting organizations from cyberattacks. In this book, you’ll get to grips with Python secure coding techniques to improve your ability to recognize dangers quickly and take appropriate action. As you progress, you’ll be well on your way to handling the contemporary challenges in the field of cybersecurity using Python, as well as protecting your digital environment from growing attacks.By the end of this book, you’ll have a solid understanding of sophisticated offensive security methods and be able to stay ahead in the constantly evolving cybersecurity space.