Ten Years Later

Alexandre Dumas

The dArtagnan Romances are a set of three novels by Alexandre Dumas telling the story of the musketeer dArtagnan from his humble beginnings in Gascony to his death as a marshal of France in the Siege of Maastricht in 1673. It is May 1660 and the fate of nations is at stake. Mazarin plots, Louis XIV is in love, and Raoul de Bragelonne, son of Athos, is intent on serving France and winning the heart of Louise de la Valliere. DArtagnan, meanwhile, is perplexed by a mysterious stranger, and soon he learns that his old comrades already have great projects in hand. Athos seeks the restoration of Charles II, while Aramis, with Porthos in tow, has a secret plan involving a masked prisoner and the fortification of the island of Belle-Ile. DArtagnan finds a thread leading him to the French court, the banks of the Tyne, the beaches of Holland, and the dunes of Brittany. The Vicomte de Bragelonne: Ten Years Later is the 3rd and largest continuation of the Musketeer saga, following The Three Musketeers and Twenty Years After.

Tender Is the Night

F. Scott Fitzgerald

Set in the South of France in the decade after World War I, Tender Is the Night is the story of a brilliant and magnetic psychiatrist named Dick Diver who marries one of his patients, a wealthy schizophrenic, Nicole Warren; as she slowly recovers, she exhausts his vitality until he is, in Fitzgeralds words, un homme épuisé (a used-up man). The novel explores how love can be won, lost, and perverted by the myriad forces that shape our lives, including money, illness, and politics.

Teneryfa. Travelbook. Wydanie 1

Berenika Wilczyńska

Teneryfa – ta najbardziej znana kanaryjska wyspa jest nazywana „wyspą wiecznej wiosny”. Zachwyca niesamowicie bujną roślinnością i łagodnym klimatem, zachęcając do wypoczynku przez cały rok. Błękitne wody Atlantyku i górujący nad wyspą wulkan Pico del Teide dostarczą niezapomnianych wrażeń zarówno amatorom błogiego lenistwa, jak i bardziej aktywnym: nurkującym i surfującym, wędrującym i jeżdżącym konno. Miłośnicy historii odkryją liczne zabytki, a smakosze - wyśmienitą kanaryjską kuchnię. Aż chciałoby się zatrzymać czas! Travelbook to Twój niezastąpiony towarzysz podróży. Wskaże najważniejsze atrakcje, podpowie, czego szukać poza głównymi szlakami, i wprowadzi w świat miejscowych obyczajów. Znajdziesz w nim opisy najciekawszych regionów i miast, a sprawdzone informacje praktyczne umożliwią staranne zaplanowanie podróży. Przewodnik wspaniale uzupełniają czytelne mapy, świetne zdjęcia i liczne ramki z ciekawostkami. Wszystko to w połączeniu z poręcznym formatem i atrakcyjną szatą graficzną sprawia, że Travelbook to najlepszy wybór dla ciekawych świata.

Tengu

Graham Masterton

Opowieść o demonicznej zemście nuklearnej Japończycy ciągle pamiętają o atomowej zagładzie sprzed ponad półwiecza. W potwornie zniekształconym ciele Kappy kryje się straszliwa śmiercionośna moc, która sprawia, że na Kalifornię spadają najokrutniejsze japońskie demony. Będzie to pierwszy krok w kierunku całkowitego zniszczenia Ameryki. Tylko jeden człowiek zna plany Kappy. Czy zdoła go powstrzymać Graham Masterton urodził się w 1946 roku w Edynburgu. Pracował jako reporter i redaktor w czasopismach Mayfair i Penthouse. W roku 1976 debiutował horrorem Manitou, który stał się światowym bestsellerem. Od tego czasu napisał ponad 100 książek, które przełożono na 18 języków i wydano w 27 milionach egzemplarzy. Jego powieści otrzymały wiele międzynarodowych nagród, m.in. Edgar Allan Poe Award, Prix Julia Verlanger i Srebrny Medal West Coast Review. Oprócz horrorów Masterton pisze thrillery, powieści historyczne i romanse. Od lat zajmuje się również seksuologią. Dom Wydawniczy REBIS opublikował m.in. jego horrory: Dziedzictwo, Bazyliszek, Noc gargulców, Czerwony Hotel oraz Panika.

Tenis stołowy. Trening z wykorzystaniem dużej liczby piłek. Zbiór ćwiczeń

Ziemowit Bańkosz

Książka zawiera opis podstawowych zagadnień dotyczących przygotowania tenisisty stołowego oraz zbiór ponad 100 ćwiczeń, które dzięki formie "na wiele piłek" można stosować w treningu w czasie szeroko rozumianego przygotowania zawodników. Sprawdzone w praktyce zestawy ćwiczeń zostały opracowane niemal w całości na podstawie doświadczeń i przemyśleń autora, który jest trenerem klasy mistrzowskiej w tenisie stołowym.

Tensor Analysis for Engineers. Mastering Coordinate Systems, Transformations and Applications using Mathematics

Mercury Learning and Information, Mehrzad Tabatabaian

This book is a comprehensive guide to tensor analysis for engineers and applied scientists, focusing on practical problem-solving in Euclidean space. It covers Cartesian coordinate systems and curvilinear coordinates like cylindrical and spherical, with examples and calculations. Expanded content includes rigid body rotation, Cartesian tensors, Euler angles, and quaternion methods.The course begins with coordinate systems, moving through curvilinear systems, basis vectors, and scale factors. It covers contravariant and physical components, tensor transformations, and mixed and metric tensors. Advanced topics include gradient operators, derivative forms, Cartesian tensor transformations, and coordinate-independent equations. The book features relations for selected coordinate systems, rigid body rotation methods, and numerous worked-out examples and exercises.Mastering tensor analysis is crucial for complex engineering and science problems. This book transitions from basic concepts to advanced applications, blending theory with practical examples. Clear explanations, figures, and exercises enhance learning, making this an essential resource for tensor analysis in Euclidean space.

TensorFlow. 13 praktycznych projektów wykorzystujących uczenie maszynowe

Ankit Jain, Armando Fandango, Amita Kapoor

TensorFlow służy do projektowania i wdrażania zaawansowanych architektur głębokiego uczenia. Jego zaletami są prostota, wydajność i elastyczność. Umożliwia budowanie złożonych rozwiązań na bazie różnorodnych zbiorów danych. Co więcej, pozwala na stosowanie różnych technik uczenia nadzorowanego, nienadzorowanego oraz uczenia przez wzmacnianie. TensorFlow zmienił sposób postrzegania uczenia maszynowego. Dzięki temu środowisku każdy, kto chce uczynić z dużych zbiorów danych wiarygodne źródło wiedzy, może ten cel osiągnąć - niezależnie od tego, czy jest analitykiem danych, naukowcem, projektantem, czy pasjonatem metod sztucznej inteligencji. To książka przeznaczona dla osób, które chcą nauczyć się tworzyć całościowe rozwiązania z wykorzystaniem uczenia maszynowego. Poszczególne zagadnienia zilustrowano trzynastoma praktycznymi projektami, w których wykorzystano między innymi analizy sentymentów, przetwarzanie języka naturalnego, systemy rekomendacyjne, generatywne sieci kontradyktoryjne czy sieci kapsułowe. Pokazano, w jaki sposób używać TensorFlow z interfejsem APO Spark i wspomagać obliczenia układami GPU. Przedstawiono zastosowanie rozkładu macierzy (SVD++), modeli rankingowych i odmian splotowej sieci neuronowej. Nie zabrakło prezentacji nowych rozwiązań o dużym potencjale, takich jak sieci DiscoGAN. Dołączony do książki kod źródłowy, liczne wskazówki i porady pozwolą na płynne rozpoczęcie pracy z TensorFlow oraz innymi narzędziami do budowy sieci neuronowych. W tej książce między innymi: podstawy pracy z TensorFlow wykorzystanie TensorFlow do wizualizacji sieci neuronowych zastosowanie procesu gaussowskiego do prognozowania cen akcji wykrywanie oszukańczych transakcji za pomocą TensorFlow i Keras implementacja sieci kapsułowych w TensorFlow techniki uczenia przez wzmacnianie TensorFlow: prostota, wydajność i imponujący potencjał!

TensorFlow 1.x Deep Learning Cookbook. Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Antonio Gulli, Amita Kapoor

Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve real-life problems in the artificial intelligence domain.In this book, you will learn how to efficiently use TensorFlow, Google’s open source framework for deep learning. You will implement different deep learning networks, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs), with easy-to-follow standalone recipes. You will learn how to use TensorFlow with Keras as the backend. You will learn how different DNNs perform onsome popularly used datasets, such as MNIST, CIFAR-10, and Youtube8m. You will not only learn about the different mobile and embedded platforms supported by TensorFlow, but also how to set up cloud platforms for deep learning applications. You will also get a sneak peek at TPU architecture and how it will affect the future of DNNs.By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning,GANs, and autoencoders.

TensorFlow 2 Pocket Primer. A Quick Reference Guide for TensorFlow 2 Developers

Mercury Learning and Information, Oswald Campesato

As part of the best-selling *Pocket Primer* series, this book introduces beginners to basic machine learning algorithms using TensorFlow 2. It provides a fast-paced introduction to TensorFlow, covering core features and machine learning basics with Python code samples. An appendix includes Keras-based code samples and explores MLPs, CNNs, RNNs, and LSTMs. The chapters illustrate how to solve various tasks, encouraging further reading to deepen your knowledge.The journey begins with an introduction to TensorFlow 2, followed by essential APIs and datasets. You'll explore linear regression and classifiers, learning to apply TensorFlow to practical problems. The comprehensive appendix covers advanced topics like NLPs and deep learning architectures, enhancing your understanding of machine learning.Understanding these concepts is crucial for modern AI applications. This book transitions readers from basic TensorFlow use to advanced machine learning techniques, blending theory with practical examples. Companion files with source code and figures enhance learning, making this an essential resource for mastering TensorFlow and machine learning.

TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

Palanisamy P

With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications.Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x.By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch.

TensorFlow 2.0 Computer Vision Cookbook. Implement machine learning solutions to overcome various computer vision challenges

Jesús Martínez

Computer vision is a scientific field that enables machines to identify and process digital images and videos. This book focuses on independent recipes to help you perform various computer vision tasks using TensorFlow.The book begins by taking you through the basics of deep learning for computer vision, along with covering TensorFlow 2.x’s key features, such as the Keras and tf.data.Dataset APIs. You’ll then learn about the ins and outs of common computer vision tasks, such as image classification, transfer learning, image enhancing and styling, and object detection. The book also covers autoencoders in domains such as inverse image search indexes and image denoising, while offering insights into various architectures used in the recipes, such as convolutional neural networks (CNNs), region-based CNNs (R-CNNs), VGGNet, and You Only Look Once (YOLO). Moving on, you’ll discover tips and tricks to solve any problems faced while building various computer vision applications. Finally, you’ll delve into more advanced topics such as Generative Adversarial Networks (GANs), video processing, and AutoML, concluding with a section focused on techniques to help you boost the performance of your networks.By the end of this TensorFlow book, you’ll be able to confidently tackle a wide range of computer vision problems using TensorFlow 2.x.

TensorFlow 2.0 Quick Start Guide. Get up to speed with the newly introduced features of TensorFlow 2.0

Tony Holdroyd

TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains.By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.

TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

Abhishek Thakur, Alberto Boschetti, Luca Massaron, Alexey Grigorev, ...

TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.

TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam

Oluwole Fagbohun

The TensorFlow Developer Certificate Guide is an indispensable resource for machine learning enthusiasts and data professionals seeking to master TensorFlow and validate their skills by earning the certification. This practical guide equips you with the skills and knowledge necessary to build robust deep learning models that effectively tackle real-world challenges across diverse industries.You’ll embark on a journey of skill acquisition through easy-to-follow, step-by-step explanations and practical examples, mastering the craft of building sophisticated models using TensorFlow 2.x and overcoming common hurdles such as overfitting and data augmentation. With this book, you’ll discover a wide range of practical applications, including computer vision, natural language processing, and time series prediction.To prepare you for the TensorFlow Developer Certificate exam, it offers comprehensive coverage of exam topics, including image classification, natural language processing (NLP), and time series analysis. With the TensorFlow certification, you’ll be primed to tackle a broad spectrum of business problems and advance your career in the exciting field of machine learning. Whether you are a novice or an experienced developer, this guide will propel you to achieve your aspirations and become a highly skilled TensorFlow professional.

TensorFlow Machine Learning Cookbook. Over 60 practical recipes to help you master Google’s TensorFlow machine learning library

Nick McClure

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

TensorFlow Machine Learning Cookbook. Over 60 recipes to build intelligent machine learning systems with the power of Python - Second Edition

Nick McClure

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.