Practical Data Analysis. For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that

Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle.Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered.Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends' network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB. Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.

Computer Architecture with Python and ARM. Learn how computers work, program your own, and explore assembly language on Raspberry Pi

Alan Clements

This comprehensive guide offers a unique and immersive learning experience by combining Python programming with ARM architecture.Starting with an introduction to computer architecture and the flow of data within a computer system, you’ll progress to building your own interpreter using Python. You’ll see how this foundation enables the simulation of computer operations and learn ways to enhance a simulator by adding new instructions and displaying improved results.As you advance, you’ll explore the TC1 Assembler and Simulator Program to gain insights into instruction analysis and explore practical examples of simulators. This will help you build essential skills in understanding complex computer instructions, strengthening your grasp of computer architecture. Moreover, you’ll be introduced to the Raspberry Pi operating system, preparing you to delve into the detailed language of the ARM computer. This includes exploring the ARM instruction set architecture, data-processing instructions, subroutines, and the stack.With clear explanations, practical examples, and coding exercises, this resource will enable you to design and construct your own computer simulator, simulate assembly language programs, and leverage the Raspberry Pi for ARM programming.

VMware Performance and Capacity Management. Click here to enter text. - Second Edition

Iwan 'e1' Rahabok

Performance management and capacity management are the two top-most issues faced by enterprise IT when doing virtualization. Until the first edition of the book, there was no in-depth coverage on the topic to tackle the issues systematically. The second edition expands the first edition, with added information and reorganizing the book into three logical parts.The first part provides the technical foundation of SDDC Management. It explains the difference between a software-defined data center and a classic physical data center, and how it impacts both architecture and operations. From this strategic view, it zooms into the most common challenges—performance management and capacity management. It introduces a new concept called Performance SLA and also a new way of doing capacity management. The next part provides the actual solution that you can implement in your environment. It puts the theories together and provides real-life examples created together with customers. It provides the reasons behind each dashboard, so that you get the understanding on why it is required and what problem it solves.The last part acts as a reference section. It provides a complete reference to vSphere and vRealize Operations counters, explaining their dependencies and providing practical guidance on the values you should expect in a healthy environment.

Learning iOS UI Development. Implement complex iOS user interfaces with ease using Swift

Justin Stenning, Yari D'areglia, Jonathan Grant

Through this comprehensive one-stop guide, you’ll get to grips with the entire UIKit framework and in a flash, you’ll be creating modern user interfaces for your iOS devices using Swift.Starting with an overview of the iOS drawing system and the available tools, you will then learn how to use these technologies to create adaptable layouts and custom elements for your applications. Next, you’ll be introduced to other topics such as animation and code-drawing with Core Graphics, which will give you all the knowledge you need to create astonishing user interfaces.By the end of this book, you will have a solid foundation in iOS user interface development and will have gained valuable insights on the process of building firm and complex UIs.

Mastering Android Game Development. Master game development with the Android SDK to develop highly interactive and amazing games

Raul Portales

Cloudera Administration Handbook. A complete, hands-on guide to building and maintaining large Apache Hadoop clusters using Cloudera Manager and CDH5

Rohit Menon

DevSecOps in Practice with VMware Tanzu. Build, run, and manage secure multi-cloud apps at scale on Kubernetes with the Tanzu portfolio

Parth Pandit, Robert Hardt

As Kubernetes (or K8s) becomes more prolific, managing large clusters at scale in a multi-cloud environment becomes more challenging – especially from a developer productivity and operational efficiency point of view. DevSecOps in Practice with VMware Tanzu addresses these challenges by automating the delivery of containerized workloads and controlling multi-cloud Kubernetes operations using Tanzu tools.This comprehensive guide begins with an overview of the VMWare Tanzu platform and discusses its tools for building useful and secure applications using the App Accelerator, Build Service, Catalog service, and API portal. Next, you’ll delve into running those applications efficiently at scale with Tanzu Kubernetes Grid and Tanzu Application Platform. As you advance, you’ll find out how to manage these applications, and control, observe, and connect them using Tanzu Mission Control, Tanzu Observability, and Tanzu Service Mesh. Finally, you’ll explore the architecture, capabilities, features, installation, configuration, implementation, and benefits of these services with the help of examples.By the end of this VMware book, you’ll have gained a thorough understanding of the VMWare Tanzu platform and be able to efficiently articulate and solve real-world business problems.

Learning Python for Forensics. Learn the art of designing, developing, and deploying innovative forensic solutions through Python

Preston Miller, Chapin Bryce

This book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer.Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.