Robotic Process Automation with Blue Prism Quick Start Guide. Create software robots and automate business processes

Lim Mei Ying

Robotic process automation is a form of business process automation where user-configured robots can emulate the actions of users. Blue Prism is a pioneer of robotic process automation software, and this book gives you a solid foundation to programming robots with Blue Prism. If you've been tasked with automating work processes, but don't know where to start, this is the book for you!You begin with the business case for robotic process automation, and then move to implementation techniques with the leading software for enterprise automation, Blue Prism. You will become familiar with the Blue Prism Studio by creating your first process. You will build upon this by adding pages, data items, blocks, collections, and loops. You will build more complex processes by learning about actions, decisions, choices, and calculations. You will move on to teach your robot to interact with applications such as Internet Explorer. This can be used for spying elements that identify what your robot needs to interact with on the screen.You will build the logic behind a business objects by using read, write, and wait stages. You will then enable your robot to read and write to Excel and CSV files. This will finally lead you to train your robot to read and send emails in Outlook. You will learn about the Control Room, where you will practice adding items to a queue, processing the items and updating the work status.Towards the end of this book you will also teach your robot to handle errors and deal with exceptions. The book concludes with tips and coding best practices for Blue Prism.

Machine Learning for Healthcare Analytics Projects. Build smart AI applications using neural network methodologies across the healthcare vertical market

Eduonix Learning Solutions

Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics.This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks.By the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain.

Network Vulnerability Assessment. Identify security loopholes in your network’s infrastructure

Sagar Rahalkar

The tech world has been taken over by digitization to a very large extent, and so it’s become extremely important for an organization to actively design security mechanisms for their network infrastructures. Analyzing vulnerabilities can be one of the best ways to secure your network infrastructure.Network Vulnerability Assessment starts with network security assessment concepts, workflows, and architectures. Then, you will use open source tools to perform both active and passive network scanning. As you make your way through the chapters, you will use these scanning results to analyze and design a threat model for network security. In the concluding chapters, you will dig deeper into concepts such as IP network analysis, Microsoft Services, and mail services. You will also get to grips with various security best practices, which will help you build your network security mechanism.By the end of this book, you will be in a position to build a security framework fit for an organization.

Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently

Christopher Bourez

This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU.The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy.The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets.

Docker Orchestration. Click here to enter text

Randall Smith

Docker orchestration is what you need when transitioning from deploying containers individually on a single host to deploying complex multi-container apps on many machines.This book covers the new orchestration features of Docker 1.12 and helps you efficiently build, test, and deploy your application using Docker. You will be shown how to build multi-container applications using Docker Compose. You will also be introduced to the building blocks for multi-host Docker clusters such as registry, overlay networks, and shared storage using practical examples. This book gives an overview of core tools such as Docker Machine, Swarm, and Compose which will enhance your orchestration skills. You’ll learn how to set up a swarm using the decentralized building block. Next, you’ll be shown how to make the most out of the in-built orchestration feature of Docker engine and you’ll use third-party tools such as Kubernetes, Mesosphere, and CoreOS to orchestrate your existing process. Finally, you will learn to deploy cluster hosts on cloud services and automate your infrastructure.

Learning Ceph. Unifed, scalable, and reliable open source storage solution - Second Edition

Karan Singh, Vaibhav Bhembre, Anthony D'Atri

Learning Ceph, Second Edition will give you all the skills you need to plan, deploy, and effectively manage your Ceph cluster. You will begin with the first module, where you will be introduced to Ceph use cases, its architecture, and core projects. In the next module, you will learn to set up a test cluster, using Ceph clusters and hardware selection. After you have learned to use Ceph clusters, the next module will teach you how to monitor cluster health, improve performance, and troubleshoot any issues that arise. In the last module, you will learn to integrate Ceph with other tools such as OpenStack, Glance, Manila, Swift, and Cinder.By the end of the book you will have learned to use Ceph effectively for your data storage requirements.

Jira 8 Essentials. Effective issue management and project tracking with the latest Jira features - Fifth Edition

Patrick Li

Atlassian Jira enables effective bug tracking for your software and mobile applications and provides tools to track and manage tasks for your projects. Jira Essentials is a comprehensive guide, now updated to Jira 8 to include enhanced features such as updates to Scrum and Kanban UI, additional search capabilities, and changes to Jira Service Desk.The book starts by explaining how to plan and set up a new Jira 8 instance from scratch before getting you acquainted with key features such as emails, workflows, business processes, and much more. You'll then understand Jira's data hierarchy and how to design and work with projects.Since Jira is used for issue management, this book delves into the different issues that can arise in your projects. You’ll explore fields, including custom fields, and learn to use them for more effective data collection. You’ll create new screens from scratch and customize them to suit your requirements. The book also covers workflows and business processes, and guides you in setting up incoming and outgoing mail servers. Toward the end, you’ll study Jira's security model and Jira Service Desk, which allows you to run Jira as a support portal.By the end of this Jira book, you will be able to implement Jira 8 in your projects with ease.

R Data Analysis Cookbook. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition

Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan

Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data.This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way.By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios.