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

Learn Java with Projects. A concise practical guide to learning everything a Java professional really needs to know

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.

Machine Learning Using TensorFlow Cookbook. Create powerful machine learning algorithms with TensorFlow

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.

The Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics

Mario Döbler, Tim Großmann

Do you want to transform data into captivating images? Do you want to make it easy for your audience to process and understand the patterns, trends, and relationships hidden within your data?The Data Visualization Workshop will guide you through the world of data visualization and help you to unlock simple secrets for transforming data into meaningful visuals with the help of exciting exercises and activities.Starting with an introduction to data visualization, this book shows you how to first prepare raw data for visualization using NumPy and pandas operations. As you progress, you’ll use plotting techniques, such as comparison and distribution, to identify relationships and similarities between datasets. You’ll then work through practical exercises to simplify the process of creating visualizations using Python plotting libraries such as Matplotlib and Seaborn. If you’ve ever wondered how popular companies like Uber and Airbnb use geoplotlib for geographical visualizations, this book has got you covered, helping you analyze and understand the process effectively. Finally, you’ll use the Bokeh library to create dynamic visualizations that can be integrated into any web page.By the end of this workshop, you’ll have learned how to present engaging mission-critical insights by creating impactful visualizations with real-world data.

Gnucash 2.4 Small Business Accounting: Beginner's Guide. Manage your accounts with this desktop financial manager application

Ashok Ramachandran, Christian Stimming

Attention, small business owners! Stop tax-day stress. Stop procrastinating with a shoebox full of receipts. Stop reinventing the wheel with a spreadsheet. Stop making decisions simply on a hunch. Stop wasting money on software that is overkill. Start by downloading GnuCash and getting your accounts in order. Designed to be easy to use, yet powerful and flexible, GnuCash allows you to track bank accounts, income, and expenses. As quick and intuitive to use as a checkbook register, it is based on professional accounting principles to ensure balanced books and accurate reports. You can do it and Gnucash 2.4 Small Business Accounting Beginner's Guide will help you get up and running with maintaining your accounts.Gnucash 2.4 Small Business Accounting Beginner's Guide speaks business language, not accountant-speak, because it is written by a former small business owner. It guides you to use GnuCash from scratch with step-by-step tutorials without jargon, pointing out the gotchas to avoid with lots of tips. It will teach you to work on routine business transactions while migrating transaction data from other applications gradually. You will be able to keep on top of transactions and run reports after reading just three chapters!Beyond Chapter 3, it is up to you how far you want to go. Reconcile with your bank and credit card statements. Charge and pay sales tax. Do invoicing. Track payments due. Set up reminders for bills. Avoid stress at tax time. Print checks. Capture expenses using your mobile phone.Gnucash 2.4 Small Business Accounting Beginner's Guide gives you the power. Know your numbers. Make decisions with confidence. Drive your business to its full potential.

IBM InfoSphere Replication Server and Data Event Publisher. Design, implement, and monitor a successful Q replication and Event Publishing project

Pav Kumar-Chatterjee, Pav Kumar Chatterjee

Business planning is no longer just about defining goals, analyzing critical issues, and then creating strategies. You must aid business integration by linking changed-data events in DB2 databases on Linux, UNIX, and Windows with EAI solutions , message brokers, data transformation tools, and more. Investing in this book will save you many hours of work (and heartache) as it guides you around the many potential pitfalls to a successful conclusion.This book will accompany you throughout your Q replication journey. Compiled from many of author's successful projects, the book will bring you some of the best practices to implement your project smoothly and within time scales. The book has in-depth coverage of Event Publisher, which publishes changed-data events that can run updated data into crucial applications, assisting your business integration processes. Event Publisher also eliminates the hand coding typically required to detect DB2 data changes that are made by operational applications.We start with a brief discussion on what replication is and the Q replication release currently available in the market. We then go on to explore the world of Q replication in more depth. The latter chapters cover all the Q replication components and then talk about the different layers that need to be implemented—the DB2 database layer, the WebSphere MQ layer, and the Q replication layer. We conclude with a chapter on how to troubleshoot a problem. The Appendix (available online) demonstrates the implementation of 13 Q replication scenarios with step-by-step instructions.

Linux Kernel Debugging. Leverage proven tools and advanced techniques to effectively debug Linux kernels and kernel modules

Kaiwan N. Billimoria

The Linux kernel is at the very core of arguably the world’s best production-quality OS. Debugging it, though, can be a complex endeavor.Linux Kernel Debugging is a comprehensive guide to learning all about advanced kernel debugging. This book covers many areas in-depth, such as instrumentation-based debugging techniques (printk and the dynamic debug framework), and shows you how to use Kprobes. Memory-related bugs tend to be a nightmare – two chapters are packed with tools and techniques devoted to debugging them. When the kernel gifts you an Oops, how exactly do you interpret it to be able to debug the underlying issue? We’ve got you covered. Concurrency tends to be an inherently complex topic, so a chapter on lock debugging will help you to learn precisely what data races are, including using KCSAN to detect them. Some thorny issues, both debug- and performance-wise, require detailed kernel-level tracing; you’ll learn to wield the impressive power of Ftrace and its frontends. You’ll also discover how to handle kernel lockups, hangs, and the dreaded kernel panic, as well as leverage the venerable GDB tool within the kernel (KGDB), along with much more.By the end of this book, you will have at your disposal a wide range of powerful kernel debugging tools and techniques, along with a keen sense of when to use which.

R: Mining spatial, text, web, and social media data. Create and customize data mining algorithms

Nathan H. Danneman, Richard Heimann, Pradeepta Mishra, Bater Makhabel

Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects.After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data.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:? Learning Data Mining with R by Bater Makhabel ? R Data Mining Blueprints by Pradeepta Mishra? Social Media Mining with R by Nathan Danneman and Richard Heimann