BIRT 2.6 Data Analysis and Reporting. Create, Design, Format, and Deploy Reports with the world's most popular Eclipse-based Business Intelligence and Reporting Tool

John Ward

BIRT is an Eclipse-based open source reporting system for web applications based on Java and Java EE. To address a wide range of reporting needs within a typical application, ranging from operational or enterprise reporting to multi-dimensional online analytical processing (OLAP), you need to know BIRT from head to toe. If you wish to start making reports easily and quickly, and also want to be up-to-date with the latest developments in BIRT, then this book is for you. It will guide you from scratch to develop reports using the Eclipse BIRT project. You will learn how to connect to data, use report items to display and format data, and use scripting to build advanced reports and charts.The book steers you through each step of report setup, to creating, designing, formatting, and deploying reports with data from a wide range of data sources. Its focus is on familiarizing you with the most visible and familiar product built with the BIRT framework – the BIRT Report Designer. It starts by introducing the concepts of business intelligence and open source software, and different installation methods. It will introduce you to the various visual report elements that can be used to design BIRT reports, such as the Palette and Grid components. You will learn the details of the data components of BIRT (the Data Source and the Data Set), different types of source data that BIRT supports such as XML files, flat text files, and databases, and the creation of all of the elements while connecting to Data Sources in reports and Report Projects. By the end of the book, you will be able to enhance the presentation of your report using Charts, Hyperlinks, and Drill Through. You will also be able to take advantage of the scripting capabilities that BIRT has to offer with Expressions and Event Handlers and successfully deploy BIRT reports.The book includes a case study at the end along with a real-world example that runs throughout the book.

Microsoft DirectAccess Best Practices and Troubleshooting. Secure and efficient functioning of your DirectAccess environment

Jordan Krause

DirectAccess is an amazing Microsoft technology that is truly the evolution of VPN; any Microsoft-centric shop needs this technology. DirectAccess is an automatic remote access solution that takes care of everything from planning to deployment.Microsoft DirectAccess Best Practices and Troubleshooting will provide you with the precise steps you need to take for the very best possible implementation of DirectAccess in your network. You will find answers to some of the most frequently asked questions from administrators and explore unique troubleshooting scenarios that you will want to understand in case they happen to you.Microsoft DirectAccess Best Practices and Troubleshooting outlines best practices for configuring DirectAccess in any network. You will learn how to configure Manage Out capabilities to plan, administer, and deploy DirectAccess client computers from inside the corporate network. You will also learn about a couple of the lesser-known capabilities within a DirectAccess environment and the log information that is available on the client machines.This book also focuses on some specific cases that portray unique or interesting troubleshooting scenarios that DirectAccess administrators may encounter. By describing the problem, the symptoms, and the fixes to these problems, the reader will be able to gain a deeper understanding of the way DirectAccess works and why these external influences are important to the overall solution.

Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition

Eyal Wirsansky

Written by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms.After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you’ll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You’ll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications.By the end of this book, you’ll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.

Forecasting Time Series Data with Prophet. Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool - Second Edition

Greg Rafferty

Forecasting Time Series Data with Prophet will help you to implement Prophet's cutting-edge forecasting techniques to model future data with high accuracy using only a few lines of code. This second edition has been fully revised with every update to the Prophet package since the first edition was published two years ago. An entirely new chapter is also included, diving into the mathematical equations behind Prophet's models. Additionally, the book contains new sections on forecasting during shocks such as COVID, creating custom trend modes from scratch, and a discussion of recent developments in the open-source forecasting community.You'll cover advanced features such as visualizing forecasts, adding holidays and trend changepoints, and handling outliers. You'll use the Fourier series to model seasonality, learn how to choose between an additive and multiplicative model, and understand when to modify each model parameter. Later, you'll see how to optimize more complicated models with hyperparameter tuning and by adding additional regressors to the model. Finally, you'll learn how to run diagnostics to evaluate the performance of your models in production.By the end of this book, you'll be able to take a raw time series dataset and build advanced and accurate forecasting models with concise, understandable, and repeatable code.

Machine Learning with Amazon SageMaker Cookbook. 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments

Joshua Arvin Lat

Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems.This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams.By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems.

Learning Cascading. Build reliable, robust, and high-performance big data applications using the Cascading application development efficiently

Michael Covert, Victoria Loewengart

Flask Framework Cookbook. Over 80 hands-on recipes to help you create small-to-large web applications using Flask

Shalabh Aggarwal

Cloud Penetration Testing for Red Teamers. Learn how to effectively pentest AWS, Azure, and GCP applications

Kim Crawley

With AWS, Azure, and GCP gaining prominence, mastering their unique features, ecosystems, and penetration testing protocols has become an indispensable skill, which is precisely what this pentesting guide for cloud platforms will help you achieve. As you navigate through the chapters, you’ll explore the intricacies of cloud security testing and gain valuable insights into how pentesters and red teamers evaluate cloud environments effectively.In addition to its coverage of these cloud platforms, the book also guides you through modern methodologies for testing containerization technologies such as Docker and Kubernetes, which are fast becoming staples in the cloud ecosystem. Additionally, it places extended focus on penetration testing AWS, Azure, and GCP through serverless applications and specialized tools. These sections will equip you with the tactics and tools necessary to exploit vulnerabilities specific to serverless architecture, thus providing a more rounded skill set.By the end of this cloud security book, you’ll not only have a comprehensive understanding of the standard approaches to cloud penetration testing but will also be proficient in identifying and mitigating vulnerabilities that are unique to cloud environments.