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Podcasts
Edward J. Cody, Emily M. Vose, Emily Vose, Edward Cody
Oracle Hyperion Interactive Reporting is one of many products in the Oracle Business Intelligence Enterprise Edition Plus software suite, an industry-leading business intelligence platform. The primary focus of the Interactive Reporting product is to provide strong relational querying and data analysis capabilities, where the software provides significant flexibility for creating custom dashboards, interfaces, and data analysis routines through the use of JavaScript programming and built-in software functionality. While Interactive Reporting is extremely flexible, performing advanced operations in the software is complicated and requires basic programming knowledge and an advanced understanding of the software. This book continues from where The Business Analyst’s Guide to Oracle Hyperion Interactive Reporting 11 completed and provides the reader with the information to successfully execute the advanced features of the product along with examples and specific techniques applicable to everyday use.The Oracle Hyperion Interactive Reporting 11 Expert Guide provides software users and developers with many examples of the techniques used by software experts. The book begins with an introduction to leveraging advanced features of the project and an introduction to JavaScript. Dashboards are a major focus of the book with four chapters focused on building a simple to complex dashboard including functions, global objects, and syncing selections across dashboards. The book places an emphasis on learning methods for data analysis by using advanced programming and built-in functions, and a unique approach to using code to generate batch reports and exports is provided. The Dashboard Studio Optimize Utility and the Dashboard Studio Merge utility are explained in detail, and the approach to building and using a central code repository for use in dashboards and computations across multiple documents in an enterprise is demonstrated. This book will help the reader become an expert user of the software, providing the skills necessary to understand, communicate, and perform advanced level tasks. The authors’ experience in developing and supporting Interactive Reporting users is very apparent throughout each chapter of the book. While the book displays content and examples from version 11 of the software, the book is also applicable to previous versions of the software dating back to version 8, so readers not currently using Interactive Reporting 11 will find the book applicable to daily use with the product.
Data Visualization: Representing Information on Modern Web. Click here to enter text
Simon Timms, Andy Kirk, Aendrew Rininsland, Swizec Teller
Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away.This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations.In third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. By the end of this course, you will have unlocked the mystery behind successful data visualizations.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Data Visualization: a successful design process by Andy Kirk? Social Data Visualization with HTML5 and JavaScript by Simon Timms? Learning d3.js Data Visualization, Second Edition by Ændrew Rininsland and Swizec Teller
Dr. Seán Kennedy, Maaike van Putten
Learn Java with Projects bridges the gap between introductory Java guides and verbose, theoretical references. This book is crafted to build a strong foundation in Java programming, starting from the Java environment itself. It goes far beyond a superficial review of the topics; it demonstrates, with practical examples, why these fundamentals are crucial for developing a deep understanding of the language. You'll not only learn about classes and objects but also see how these concepts are used in practical scenarios, enhancing your ability to write clean, efficient code. The engaging projects throughout the book provide real-world applications of complex topics, ensuring you can connect theoretical knowledge with practical skills. What makes this book stand out is the expertise of its authors. Seán, a seasoned university lecturer with over 20 years of experience, brings academic rigor and real-world insights, thanks to his work with a prestigious software company. Maaike, a passionate software developer and award-winning trainer, brings hands-on experience and a love for teaching. By the end of this book, you'll not only understand Java's core concepts and the critical advanced ones, but also gain practical experience through projects that mimic real-life challenges.
Alexia Audevart, Konrad Banachewicz, Luca Massaron
The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. Dive into recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google’s machine learning library, TensorFlow.This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You’ll discover real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and regression.Explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be used to solve computer vision and natural language processing (NLP) problems.With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios.