Exploring Experience Design. Fusing business, tech, and design to shape customer engagement

Ezra Schwartz

We live in an experience economy in which interaction with products is valued more than owning them. Products are expected to engage and delight in order to form the emotional bonds that forge long-term customer loyalty:Products need to anticipate our needs and perform tasks for us: refrigerators order food, homes monitor energy, and cars drive autonomously; they track our vitals, sleep, location, finances, interactions, and content use; recognize our biometric signatures, chat with us, understand and motivate us. Beautiful and easy to use, products have to be fully customizable to match our personal preferences.Accomplishing these feats is easier said than done, but a solution has emerged in the form of Experience design (XD), the unifying approach to fusing business, technology and design around a user-centered philosophy.This book explores key dimensions of XD: Close collaboration among interdisciplinary teams, rapid iteration and ongoing user validation. We cover the processes, methodologies, tools, techniques and best-practices practitioners use throughout the entire product development life-cycle, as ideas are transformed to into positive experiences which lead to perpetual customer engagement and brand loyalty.

R Statistics Cookbook. Over 100 recipes for performing complex statistical operations with R 3.5

Francisco Juretig

R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools.You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making.By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry.

Testing Practitioner Handbook. Gain insights into the latest technology and business trends within testing domains

Renu Rajani

The book is based on the author`s experience in leading and transforming large test engagements and architecting solutions for customer testing requirements/bids/problem areas. It targets the testing practitioner population and provides them with a single go-to place to find perspectives, practices, trends, tools, and solutions to test applications as they face the evolving digital world. This book is divided into five parts where each part explores different aspects of testing in the real world. The first module explains the various testing engagement models. You will then learn how to efficiently test code in different life cycles. The book discusses the different aspects of Quality Analysis consideration while testing social media, mobile, analytics, and the Cloud. In the last module, you will learn about futuristic technologies to test software.By the end of the book, you will understand the latest business and IT trends in digital transformation and learn the best practices to adopt for business assurance.

Securing Network Infrastructure. Discover practical network security with Nmap and Nessus 7

Sairam Jetty, Sagar Rahalkar

Digitization drives technology today, which is why it’s so important for organizations to design security mechanisms for their network infrastructures. Analyzing vulnerabilities is one of the best ways to secure your network infrastructure.This Learning Path begins by introducing you to the various concepts of network security assessment, workflows, and architectures. You will learn to employ open source tools to perform both active and passive network scanning and use these results to analyze and design a threat model for network security. With a firm understanding of the basics, you will then explore how to use Nessus and Nmap to scan your network for vulnerabilities and open ports and gain back door entry into a network. As you progress through the chapters, you will gain insights into how to carry out various key scanning tasks, including firewall detection, OS detection, and access management to detect vulnerabilities in your network.By the end of this Learning Path, you will be familiar with the tools you need for network scanning and techniques for vulnerability scanning and network protection.This Learning Path includes content from the following Packt books:•Network Scanning Cookbook by Sairam Jetty•Network Vulnerability Assessment by Sagar Rahalkar

Reinforcement Learning with TensorFlow. A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

Sayon Dutta

Reinforcement learning (RL) allows you to develop smart, quick and self-learning systems in your business surroundings. It's an effective method for training learning agents and solving a variety of problems in Artificial Intelligence - from games, self-driving cars and robots, to enterprise applications such as data center energy saving (cooling data centers) and smart warehousing solutions.The book covers major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You'll also be introduced to the concept of reinforcement learning, its advantages and the reasons why it's gaining so much popularity. You'll explore MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, and temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP.By the end of this book, you will have gained a firm understanding of what reinforcement learning is and understand how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym.

Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition

Alexander Combs, Michael Roman

Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects.The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks.By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects.

Django RESTful Web Services. The easiest way to build Python RESTful APIs and web services with Django

Gaston C. Hillar

Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services.If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you.The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service.Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django.

Python Interviews. Discussions with Python Experts

Michael Driscoll, Kenneth Reitz

Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips.• Brett Cannon - former director of the PSF, Python core developer, led the migration to Python 3.• Steve Holden - tireless Python promoter and former chairman and director of the PSF.• Carol Willing - former director of the PSF and Python core developer, Project Jupyter Steering Council member.• Nick Coghlan - founding member of the PSF's Packaging Working Group and Python core developer.• Jessica McKellar - former director of the PSF and Python activist.• Marc-André Lemburg - Python core developer and founding member of the PSF.• Glyph Lefkowitz - founder of Twisted and fellow of the PSF• Doug Hellmann - fellow of the PSF, creator of the Python Module of the Week blog, Python community member since 1998.• Massimo Di Pierro - fellow of the PSF, data scientist and the inventor of web2py. • Alex Martelli - fellow of the PSF and co-author of Python in a Nutshell.• Barry Warsaw - fellow of the PSF, Python core developer since 1995, and original member of PythonLabs.• Tarek Ziadé - founder of Afpy and author of Expert Python Programming.• Sebastian Raschka - data scientist and author of Python Machine Learning.• Wesley Chun - fellow of the PSF and author of the Core Python Programming books.• Steven Lott - Python blogger and author of Python for Secret Agents.• Oliver Schoenborn - author of Pypubsub and wxPython mailing list contributor.• Al Sweigart - bestselling author of Automate the Boring Stuff with Python and creator of the Python modules Pyperclip and PyAutoGUI.• Luciano Ramalho - fellow of the PSF and the author of Fluent Python.• Mike Bayer - fellow of the PSF, creator of open source libraries including SQLAlchemy.• Jake Vanderplas - data scientist and author of Python Data Science Handbook.