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UX Optimization
UX Optimization

Combine two typically separate sources of data - behavioral quantitative data and usability testing qualitative data - into a powerful single tool that helps improve your organization's website by increasing conversion and ROI. The combination of the what is happening data of website activity, coupled with the why it's happening data of usability testing, provides a complete 360-degree view into what is causing poor performance, where your website can be optimized, and how it can be improved. There are plenty of books focusing on big data and using data analytics to improve websites, or on utilizing usability testing and UX research methods for improvement. This is the first book that combines both subjects into a methodology you can use over and over again to improve any website. UX Optimization is ideal for anyone who wants to combine the power of quantitative data with the insights provided by qualitative data to improve website results. The book uses step-by-step instructions ...
Cybersecurity Incident Response
Cybersecurity Incident Response

Create, maintain, and manage a continual cybersecurity incident response program using the practical steps presented in this book. Don't allow your cybersecurity incident responses (IR) to fall short of the mark due to lack of planning, preparation, leadership, and management support. Surviving an incident, or a breach, requires the best response possible. This book provides practical guidance for the containment, eradication, and recovery from cybersecurity events and incidents. The book takes the approach that incident response should be a continual program. Leaders must understand the organizational environment, the strengths and weaknesses of the program and team, and how to strategically respond. Successful behaviors and actions required for each phase of incident response are explored in the book. Straight from NIST 800-61, these actions include: Planning and practicing, Detection, Containment, Eradication, Post-incident actions. Know the sub-categories of the NIST Cyber ...
Complete Guide to Test Automation
Complete Guide to Test Automation

Rely on this robust and thorough guide to build and maintain successful test automation. As the software industry shifts from traditional waterfall paradigms into more agile ones, test automation becomes a highly important tool that allows your development teams to deliver software at an ever-increasing pace without compromising quality. Even though it may seem trivial to automate the repetitive tester's work, using test automation efficiently and properly is not trivial. Many test automation endeavors end up in the "graveyard" of software projects. There are many things that affect the value of test automation, and also its costs. This book aims to cover all of these aspects in great detail so you can make decisions to create the best test automation solution that will not only help your test automation project to succeed, but also allow the entire software project to thrive. One of the most important details that affects the success of the test automation is how easy it is to m ...
Applied Natural Language Processing with Python
Applied Natural Language Processing with Python

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment. Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim; Manipulate and preprocess raw text data in formats such as .txt and .pdf; Strengthen your skills in data science by learning both the theory and the application of various algorithms. ...
Beginning AI Bot Frameworks
Beginning AI Bot Frameworks

Want to build your first AI bot but don't know where to start? This book provides a comprehensive look at all the major bot frameworks available. You'll learn the basics for each framework in one place and get a clear picture for which one is best for your needs. Beginning AI Bot Frameworks starts with an overview of bot development and then looks at Google Wit.ai and APi.ai functions, IBM Watson, AWS bots with Lambda, FlockOS and TensorFlow. Additionally, it touches on Deep Learning and how bot frameworks can be extended to mixed reality with Hololens. By the end, you'll have mastered the different bot frameworks available and finally have the confidence to develop intelligent AI Chatbots of their own. Review key structural points for building bots; Understand the basic requirements for building a bot in each framework; Integrate some of the frameworks; Compare the features of each framework. ...
Monetizing Machine Learning
Monetizing Machine Learning

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book - Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time. Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serv ...
CompTIA Security+ Certification Guide
CompTIA Security+ Certification Guide

CompTIA Security+ is a worldwide certification that establishes the fundamental knowledge required to perform core security functions and pursue an IT security career. CompTIA Security+ Certification Guide is a best-in-class exam study guide that covers all of CompTIA Security+ 501 exam objectives. It is authored by Ian Neil, who is a world-class trainer of CompTIA Security+ 501. Packed with self-assessment scenarios and realistic exam questions, this guide will help you master the core concepts to succeed in the exam the first time you take it. Using relevant examples, you will learn all the important security fundamentals from Certificates and Encryption to Identity and Access Management concepts. You will then dive into the important domains of the exam; namely, threats, attacks and vulnerabilities, technologies and tools, architecture and design, risk management, and cryptography and Public Key Infrastructure (PKI). This book comes with over 600 practice questions with detail ...
Matplotlib 3.0 Cookbook
Matplotlib 3.0 Cookbook

Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7. With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by exten ...
Mastering Exploratory Analysis with pandas
Mastering Exploratory Analysis with pandas

The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties. This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats. By the end of this book, you will have a better understanding of exploratory analysis a ...
Mastering Predictive Analytics with scikit-learn and TensorFlow
Mastering Predictive Analytics with scikit-learn and TensorFlow

Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems. This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics. By the end of this book, you will be well-versed in usi ...
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