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Archenemies

Author: Marissa Meyer
Publisher: Feiwel & Friends
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The Renegades Trilogy continues, in this fiercely awaited second installment after the New York Times-bestselling Renegades by Marissa Meyer, author of the Lunar Chronicles. Now a New York Times Bestseller! Time is running out. Together, they can save the world. But they each other’s worst nightmare. Nova’s double life is about to get a lot more complicated: As Insomnia, she is a full-fledged member of the Renegades, a syndicate of powerful and beloved superheroes. She works with Adrian’s patrol unit to protect the weak and maintain order in Gatlon City. As Nightmare, she is an Anarchist - a group of of villains who are determined to destroy the Renegades. Nova wants vengeance against the so-called heroes who once failed her when she needed them most. But as Nova, her feelings for Adrian are deepening, despite the fact that he is the son of her sworn enemies and, unbeknownst to Nova, he has some dangerous secrets of his own. In this second installment of the Renegades trilogy, Nova, Adrian, and the rest of their crew – Ruby, Oscar, and Danna -- are faced with escalating crime in Gatlon City, while covert weapons and conflicting missions have Nova and Adrian questioning not only their beliefs about justice, but also the feelings they have for each other. The line between good and evil has been blurred, but what's clear to them both is that too much power could mean the end of their city – and the world – as they know it.


Marvel Universe Coloring Book

Author: Virginia Carlson
Publisher: Createspace Independent Publishing Platform
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Marvel counts among its characters such well-known superheroes as Spider-Man, Captain America, Hulk, Thor, Doctor Strange, Iron Man, Deadpool, Wolverine, Daredevil, Ms. Marvel, and Ant-Man, such teams as the Avengers, the Guardians of the Galaxy, the Inhumans, S.H.I.E.L.D., the Fantastic Four, and the X-Men, and antagonists such as Venom, Doctor Doom, Red Skull, Green Goblin, Thanos, Ultron, Doctor Octopus, Magneto and Loki. Most of Marvel's fictional characters operate in a single reality known as the Marvel Universe, with locations that mirror real-life cities.


Archenemy

Author: Patrick Hueller
Publisher: Darby Creek ™
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As a defender for the Fraser High girls soccer team, Addie used to be ready for anything. There was no play she couldn't shut down. But now the biggest threat on the field is one of her teammates . . . who is also Addie's former best friend. When Eva Riley moved to town, she and Addie became super close. But when Eva wanted to be more than friends, Addie put soccer first instead. Suddenly Eva's sending Addie mean notes. Then she's screwing up Addie's plays. After a while, Addie's not sure she even wants her friend back. She has to worry about other things—like keeping her spot on the team after Eva's latest act of sabotage.


Nemesis

Author: Chuck Klosterman
Publisher: Simon and Schuster
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Originally collected in Chuck Klosterman IV and now available both as a stand-alone essay and in the ebook collection Chuck Klosterman on Living and Society, this essay is about nemeses.


Supernova

Author: Marissa Meyer
Publisher: Feiwel & Friends
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All's fair in love and anarchy... Supernova, the epic conclusion to New York Times bestselling author Marissa Meyer's thrilling Renegades Trilogy finds Nova and Adrian struggling to keep their secret identities concealed while the battle rages on between their alter egos, their allies, and their greatest fears come to life. Secrets, lies, and betrayals are revealed as anarchy once again threatens to reclaim Gatlon City.


Hands On Transfer Learning with Python

Author: Dipanjan Sarkar
Publisher: Packt Publishing Ltd
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Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features Build deep learning models with transfer learning principles in Python implement transfer learning to solve real-world research problems Perform complex operations such as image captioning neural style transfer Book Description Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP). By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems. What you will learn Set up your own DL environment with graphics processing unit (GPU) and Cloud support Delve into transfer learning principles with ML and DL models Explore various DL architectures, including CNN, LSTM, and capsule networks Learn about data and network representation and loss functions Get to grips with models and strategies in transfer learning Walk through potential challenges in building complex transfer learning models from scratch Explore real-world research problems related to computer vision and audio analysis Understand how transfer learning can be leveraged in NLP Who this book is for Hands-On Transfer Learning with Python is for data scientists, machine learning engineers, analysts and developers with an interest in data and applying state-of-the-art transfer learning methodologies to solve tough real-world problems. Basic proficiency in machine learning and Python is required.


Arch Enemies

Author: James Rick
Publisher: Independently Published
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Size: 18,99 MB
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Foot health and healing! How to keep feet healthy or return back to health. Reflexology and feet exercises. Heal foot ailments.


Becoming Rivals

Author: Brandon Valeriano
Publisher: Routledge
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Rivalries are a fundamental aspect of all international interactions. The concept of rivalry suggests that historic animosity may be the most fundamental variable in explaining and understanding why states commit international violence against each other. By understanding the historic factors behind the emergence of rivalry, the strategies employed by states to deal with potential threats, and the issues endemic to enemies, this book seeks to understand and predict why states become rivals. The recent increase in the quantitative study of rivalry has largely identified who the rivals are, but not how they form and escalate. Questions about the escalation of rivalry are important if we are to understand the nature of conflictual interactions. This book addresses an important research gap in the field by directly tackling the question of rivalry formation. In addition to making new contributions to the literature, this book will summarize a cohesive model of how all interstate rivalries form by using both quantitative and qualitative methods and sources.


It s A Kid s Life Arch Enemies

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Publisher: It's a Kid's Life
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Size: 23,83 MB
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Annales Zoologici

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Size: 13,79 MB
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