This monograph illustrates important notions in security reductions and essential techniques in security reductions for group-based cryptosystems. Using digital signatures and encryption as examples, the authors explain how to program correct security reductions for those cryptographic primitives. Various schemes are selected and re-proven in this book to demonstrate and exemplify correct security reductions.
This book is suitable for researchers and graduate students engaged with public-key cryptography.
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Leverage the power of Matplotlib to visualize and understand your data more effectively Key Features Perform effective data visualization with Matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of Matplotlib in this practical guide with updated code and examples Book DescriptionPython is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations. What you will learn Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn Create interactive plots with real-time updates Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django Write data visualization code that is readily expandable on the cloud platform Who this book is forThis book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you’re a data scientist or analyst and wish to create attractive visualizations using Python, you’ll find this book useful. Some knowledge of Python programming is all you need to get started.
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We’ve become a tribe of tech addicts, and it’s not entirely our fault.
Taking advantage of vulnerabilities in the human brain function, tech companies entice us to overdose on technology interaction. This damages our lives, work, families and friendships. Swipe-driven apps train us to evaluate people like products, diminishing our relationships. At work, we email on an average of seventy-seven times a day, ruining our concentration. At home, light from our screens contributes to epidemic sleep deprivation.
But we can reclaim our lives without dismissing technology. The authors explain how to avoid getting hooked on tech and how to define and control the roles that it plays and could play in our lives. This profound and timely book turns personal observation into a handy guide to adapting to our new reality of omnipresent technology.
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Design, simulate, and program interactive robots Key Features Design, simulate, build, and program an interactive autonomous mobile robot Leverage the power of ROS, Gazebo, and Python to enhance your robotic skills A hands-on guide to creating an autonomous mobile robot with the help of ROS and Python Book DescriptionRobot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch. This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you’ll learn about robot modeling and how to design and simulate it using ROS. Moving on, we’ll design robot hardware and interfacing actuators. Then, you’ll learn to configure and program depth sensors and LIDARs using ROS. Finally, you’ll create a GUI for your robot using the Qt framework. By the end of this tutorial, you’ll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package. What you will learn Design a differential robot from scratch Model a differential robot using ROS and URDF Simulate a differential robot using ROS and Gazebo Design robot hardware electronics Interface robot actuators with embedded boards Explore the interfacing of different 3D depth cameras in ROS Implement autonomous navigation in ChefBot Create a GUI for robot control Who this book is forThis book is for those who are conducting research in mobile robotics and autonomous navigation. As well as the robotics research domain, this book is also for the robot hobbyist community. You’re expected to have a basic understanding of Linux commands and Python.
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A clear, visual guide to the technical, societal, and cultural aspects of computers and social media, using step-by-step diagrams and graphics to explore how kids can get the most from computers while staying safe.
Covering everything from data to digital life, from computer coding to cyber attacks, this unique guide gives parents and kids the most up-to-date and comprehensive facts and information in a visually appealing way. It examines the technical aspects of computers, such as how they function, the latest digital devices and software, and how the Internet works. It also builds the confidence of parents and kids when facing challenges such as staying safe online, digital etiquette, and how to navigate the potential pitfalls of social media. Jargon-free language helps to explain difficult and potentially dread-inducing concepts such as hacking, Bitcoin, and malware, while colorful graphics help make learning about the world of computer science exciting. For those who want to make the most out of the digital world, Help Your Kids with Computer Science is the perfect platform to discover more.
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As more and more iOS devices are reaching world markets, it’s becoming more important to make sure your apps work properly in those markets. Pro iOS Internationalization and Localization is a concise and very practical guide to making sure your apps are usable no matter where your users may live, and no matter what languages they may speak.
You’ll learn how to localize text, timezones, and even graphics to fit your audience. You’ll go beyond Xcode to learning not only how to script your internationalization, but also how to work with language experts to make sure you get it just right.
If you have an app or a set of apps, and you want to reach that world market with no distractions about other topics, then Pro iOS Internationalization and Localization is exactly the book you need.
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Python machine learning: a guide for beginners
This book contains:
Machine learning: a guide for beginners
Python: A Complete Step By Step Beginners Guide To Programming With Python
What exactly is machine learning and why is it so valuable in the online business world? Simply put, it is a method of data analysis that uses algorithms that learn from data and produce specific results without being specifically programmed to do so. These algorithms can analyze data, calculate how frequently certain parts of it are used and generate responses based on this calculations in order to automatically interact with users.
The main topics:
What does Machine Learning mean Machine Learning And Artificial Intelligence Some of the branches of Artificial Intelligence Decision trees in relation to Machine Learning What Python is and how to get started with it What input and output mean in Python The way that Python evolved throughout time
After reading this book, you will be able to write simple codes using Python. You will also know the direction that you should go after you have surpassed the beginner level of Python.
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Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow Key Features Learn reinforcement learning concepts and their implementation using TensorFlow Discover different problem-solving methods for Reinforcement Learning Apply reinforcement learning for autonomous driving cars, robobrokers, and more Book DescriptionReinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence-from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it’s gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, 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 a firm understanding of what reinforcement learning is and how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym. What you will learn Implement state-of-the-art Reinforcement Learning algorithms from the basics Discover various techniques of Reinforcement Learning such as MDP, Q Learning and more Learn the applications of Reinforcement Learning in advertisement, image processing, and NLP Teach a Reinforcement Learning model to play a game using TensorFlow and the OpenAI gym Understand how Reinforcement Learning Applications are used in robotics Who this book is forIf you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience with Reinforcement Learning is required.
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Volume 2 has arrived! We all know sequels are never as good (unless it’s a Godfather movie) but don’t judge too harshly.
Like Volume 1 this book is a light-hearted look at some useful Sitecore tips (current version is 9.0 rev. 171219 Update-1).
These tips are targeted at all levels of user but whether you’re recapping or learning, I hope you find the book useful.
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This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (RL), from the first principles to the latest algorithms Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms Keep up with the very latest industry developments, including AI-driven chatbots Book DescriptionRecent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google’s use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on `grid world’ environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. What you will learn Understand the DL context of RL and implement complex DL models Learn the foundation of RL: Markov decision processes Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others Discover how to deal with discrete and continuous action spaces in various environments Defeat Atari arcade games using the value iteration method Create your own OpenAI Gym environment to train a stock trading agent Teach your agent to play Connect4 using AlphaGo Zero Explore the very latest deep RL research on topics including AI-driven chatbots Who this book is forSome fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL.
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