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The Conglomerate’s most dangerous convicts have made the prison ship Perdition their home. And they will defend it…
Perdition is under siege. Mercenaries have boarded the station with orders to take control of the facility—and execute the prisoners. Their commander is offering full pardons to the first five inmates willing to help the mercs complete their mission.
Dresdemona “Dred” Devos hasn’t survived hard time just to surrender to the Conglomerate’s armored thugs. Leading a ragtag army of inmates, Dred and her champion, Jael, wage a bloody guerilla war of chaos and carnage against impossible odds. But no matter how dire the outlook, the Dread Queen never backs down…
Książka ma 320 stron.


Sometimes revenge is best paid in cold steel.
Joe Kurtz has been wronged one too many times. So when he takes out the drugdealing thug who killed his girlfriend, the exPI gets to cool his heels for 11 years in Attica. It’s there that he meets “Little Skag” Farino, the son of an aging Buffalo, New York, mob boss. In exchange for protecting the kid’s manhood against any unwanted jailhouse affection, Kurtz gets an audience with Little Skag’s father upon his release from prison.
Semiretired Don Byron Farino is still clinging to what dwindling power he holds on the New York organized crime scene. He enlists Kurtz’s help to track down the Family’s missing accountanta man with too much knowledge of Family business to have on the loose. But someone doesn’t want the accountant found. As the story twists and turns and the body count rises, Kurtz no longer knows whom he can trust. Everyone seems to be after something, from the mob boss’s sultry yet dangerous daughter, to a hit man named The Dane, an albino killer who is good with a knife, and a dwarf who is armed to the teeth and hellbent on revenge.
Bestselling author Dan Simmons expertly builds the tension as he springs one surprise after another, all the while daring the reader to take a ride with Kurtz through the cold, windy streets of Buffalo where one wrong move could mean a bellyfull of lead.

Hans Christian Andersen’s Fairy Tales: Selected and Illustrated by Lisbeth Zwerger

Os Contos escolhidos para este livro são dos mais conhecidos – e também dos menos conhecidos… Em todos eles, no entanto, se encontra o grande poder de contador de histórias de Andersen, a poesia, a viva descrição da paisagem, o seu grande sentido de humor, as histórias em que se movimentam não apensas pessoas ou seres fantásticos mas também objectos, coisas inanimadas. ** Os Contos escolhidos para este livro são dos mais conhecidos – e também dos menos conhecidos… Em todos eles, no entanto, se encontra o grande poder de contador de histórias de Andersen, a poesia, a viva descrição da paisagem, o seu grande sentido de humor, as histórias em que se movimentam não apensas pessoas ou seres fantásticos mas também objectos, coisas inanimadas.
Contos reunidos neste livro:
\- A Princesa e a Ervilha
\- A Polegarzinha
\- O Fato Novo do Imperador
\- A Sereiazinha
\- O Firme Soldado de Chumbo
\- O Rouxinol
\- O Patinho Feio
\- A Rainha da Neve
\- A Pastora e o Limpa-chaminés
\- A Família Feliz
\- O Duende da Mercearia
\- Dança, Dança, Bonequinha …more **

Hands-On Web Scraping with Python

Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques

Key Features

  • Learn various scraping techniques using a range of Python libraries such as Scrapy and Beautiful Soup
  • Build scrapers and crawlers to extract relevant information from the web
  • Automate web scraping operations to bridge the accuracy gap and ease complex business needs

    Book Description

    Web scraping is an essential technique used in many organizations to scrape valuable data from web pages. This book will enable you to delve deeply into web scraping techniques and methodologies.

    This book will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. We’ll use powerful libraries from the Python ecosystem—such as Scrapy, lxml, pyquery, bs4, and others—to carry out web scraping operations. We will take an in-depth look at…

  • Hands-on Scikit-Learn for Machine Learning Applications

    Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine.
    All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complex machine learning…

    Hands-On Robotics Programming with C++

    Enhance your programming skills to build exciting robotic projects

    Key Features

  • Build an intelligent robot that can detect and avoid obstacles and respond to voice commands
  • Detect and track objects and faces using OpenCV
  • Control your robot with a GUI button designed using Qt5

    Book Description

    C++ is one of the most popular legacy programming languages for robotics, and a combination of C++ and robotics hardware is used in many leading industries. This book will bridge the gap between Raspberry Pi and C/C++ programming and enable you to develop applications for Raspberry Pi. To follow along with the projects covered in the book, you can implement C programs in Raspberry Pi with the wiringPi library.

    With this book, you’ll develop a fully functional car robot and write programs to move it in different directions. You’ll then create an obstacle – avoiding robot using an ultrasonic sensor. Furthermore, you’ll find out how to control the robot…

  • Hands-On Reinforcement Learning With Python

    **A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python**
    #### Key Features
    * Your entry point into the world of artificial intelligence using the power of Python
    * An example-rich guide to master various RL and DRL algorithms
    * Explore various state-of-the-art architectures along with math

    #### Book Description
    Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.
    The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning.
    By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence.
    #### What you will learn
    * Understand the basics of reinforcement learning methods, algorithms, and elements
    * Train an agent to walk using OpenAI Gym and Tensorflow
    * Understand the Markov Decision Process, Bellman’s optimality, and TD learning
    * Solve multi-armed-bandit problems using various algorithms
    * Master deep learning algorithms, such as RNN, LSTM, and CNN with applications
    * Build intelligent agents using the DRQN algorithm to play the Doom game
    * Teach agents to play the Lunar Lander game using DDPG
    * Train an agent to win a car racing game using dueling DQN

    #### Who this book is for
    If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book.

    Hands-On Qt for Python Developers

    **Boost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2.**
    #### Key Features
    * Build optimized GUI applications by implementing multiprocessing and concurrency
    * Understand embedded and mobile development with PyQt and PySide
    * Learn to create magnificent GUI applications using Pyside2 and QtQuick/QML

    #### Book Description
    Qt is one of the most widely used and flexible frameworks for GUI application development, allowing you to write your application once and then deploy it to multiple operating systems. This book combines the best of Python and Qt to help you develop GUI applications with Python bindings, such as PyQt and PySide, that will supercharge your Python applications.
    The book begins with an overview of Qt and QML. You’ll start by working with PyQt GUI elements to style your applications. Then, you will learn how to use QWidget, frames, labels, and text fields, and work with graphics. This will be followed by taking you through how elements in the application communicate with each other by understanding signals, slots, and event handlers. This book will help you to gain a better understanding of the Qt framework and the tools to resolve issues when testing, linking, debugging, and multithreading your Python GUI applications. Finally, the book will help you get to grips with embedded and mobile development using PyQt and PySide.
    By the end of the book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML.
    #### What you will learn
    * Explore PyQt5 and PySide2 to create comprehensive GUI applications
    * Find out how threading and multiprocessing work
    * Understand how to style GUIs with PyQt
    * Get to grips with implementing buttons
    * Understand how elements communicate with signals, slots, and event handlers
    * Explore mobile development with PyQt and PySide

    #### Who this book is for
    This book is for Python developers who want to develop GUIs and cross-platform applications that are modern, responsive, and attractive. No prior knowledge of Qt or QML is required.

    Hands-On Python for Finance

    Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras

    Key Features

  • Understand Python data structure fundamentals and work with time series data
  • Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance
  • Explore various Python programs and learn finance paradigms

    Book Description

    Python is one of the most popular languages used for quantitative finance. With this book, you’ll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management.

    The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you’ll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and…

  • Hands-On Neural Networks With TensorFlow 2.0

    **A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0**
    #### Key Features
    * Understand the basics of machine learning and discover the power of neural networks and deep learning
    * Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0
    * Solve any deep learning problem by developing neural network-based solutions using TF 2.0

    #### Book Description
    TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you’ll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers.
    This book covers machine learning with a focus on developing neural network-based solutions. You’ll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you’ll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub.
    By the end of this TensorFlow book, you’ll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production.
    #### What you will learn
    * Grasp machine learning and neural network techniques to solve challenging tasks
    * Apply the new features of TF 2.0 to speed up development
    * Use TensorFlow Datasets (tfds) and the API to build high-efficiency data input pipelines
    * Perform transfer learning and fine-tuning with TensorFlow Hub
    * Define and train networks to solve object detection and semantic segmentation problems
    * Train Generative Adversarial Networks (GANs) to generate images and data distributions
    * Use the SavedModel file format to put a model, or a generic computational graph, into production

    #### Who this book is for
    If you’re a developer who wants to get started with machine learning and TensorFlow, or a data scientist interested in developing neural network solutions in TF 2.0, this book is for you. Experienced machine learning engineers who want to master the new features of the TensorFlow framework will also find this book useful.
    Basic knowledge of calculus and a strong understanding of Python programming will help you grasp the topics covered in this book.

    Hands-On Network Forensics

    Gain basic skills in network forensics and learn how to apply them effectively

    Key Features

  • Investigate network threats with ease
  • Practice forensics tasks such as intrusion detection, network analysis, and scanning
  • Learn forensics investigation at the network level

    Book Description

    Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities.

    Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis,…