Big data
Kathrin Melcher, Rosaria Silipo
KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.
Kathrin Melcher, Rosaria Silipo
KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.
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 book will be tested with the mock tests that appear in the final chapters.By the end of this book, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.
J. Ashley Hunt
The CompTIA Project+ exam is designed for IT professionals who want to improve their career trajectory by gaining certification in project management specific to their industry. This guide covers everything necessary to pass the current iteration of the Project+ PK0-004 exam.The CompTIA Project+ Certification Guide starts by covering project initiation best practices, including an understanding of organizational structures, team roles, and responsibilities. You’ll then study best practices for developing a project charter and the scope of work to produce deliverables necessary to obtain formal approval of the end result. The ability to monitor your project work and make changes as necessary to bring performance back in line with the plan is the difference between a successful and unsuccessful project. The concluding chapters of the book provide best practices to help keep an eye on your projects and close them out successfully. The guide also includes practice questions created to mirror the exam experience and help solidify your understanding of core project management concepts.By the end of this book, you will be able to develop creative solutions for complex issues faced in project management.
Ian Neil
CompTIA Security+ is a worldwide certification that establishes the fundamental knowledge required to perform core security functions and pursue an IT security career. CompTIA Security+ Certification Guide is a best-in-class exam study guide that covers all of CompTIA Security+ 501 exam objectives. It is authored by Ian Neil, who is a world-class trainer of CompTIA Security+ 501. Packed with self-assessment scenarios and realistic exam questions, this guide will help you master the core concepts to succeed in the exam the first time you take it. Using relevant examples, you will learn all the important security fundamentals from Certificates and Encryption to Identity and Access Management concepts. You will then dive into the important domains of the exam; namely, threats, attacks and vulnerabilities, technologies and tools, architecture and design, risk management, and cryptography and Public Key Infrastructure (PKI). This book comes with over 600 practice questions with detailed explanation that is at the exam level and also includes two mock exams to help you with your study plan. This guide will ensure that encryption and certificates are made easy for you.
Ian Neil
CompTIA Security+ is a core security certification that will validate your baseline skills for a career in cybersecurity. Passing this exam will not only help you identify security incidents but will also equip you to resolve them efficiently. This book builds on the popular CompTIA Security+ Certification Guide, which mirrors the SY0-501 exam pattern.This practice test-based guide covers all six domains of the Security+ SY0-501 exam: threats, attacks, and vulnerabilities; technologies and tools; architecture and design; identity and access management; cryptography and PKI; and risk management. You’ll take six mock tests designed as per the official Security+ certification exam pattern, each covering significant aspects from an examination point of view. For each domain, the book provides a dedicated cheat sheet that includes important concepts covered in the test. You can even time your tests to simulate the actual exam. These tests will help you identify gaps in your knowledge and discover answers to tricky exam questions.By the end of this book, you’ll have developed and enhanced the skills necessary to pass the official CompTIA Security+ exam.
Computational Physics. A Comprehensive Guide to Numerical Methods in Physics
Mercury Learning and Information, Darren Walker
This updated edition introduces computational physics for performing experiments on the computer. It provides a grounding in scientific programming with examples in the context of physics problems. Using C++ as the primary language, it covers interpolation, integration, and solving differential equations, from simple concepts to advanced topics. The book includes a chapter on high-performance computing and parallel programming.Understanding computational physics is crucial for data manipulation and real-world simulations. The book starts with introductory topics and progresses to advanced material, including a C++ library and sample programs. Readers will learn problem-solving methods and constructing models.This journey equips readers with skills for scientific tasks, demonstrating efficient problem-solving and model construction. The practical approach ensures users can apply these concepts in real-world scenarios, making it an essential resource for those interested in computational physics.
Lauren Mullennex, Nate Bachmeier, Jay Rao
Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models.You’ll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that’ll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads.By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.
Matthew Rever
Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.