Bücher von David Foster

Generative modeling is one of the hottest topics in AI. Its now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models.Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, youll understand how to make your models learn more efficiently and become more creative.Discover how variational autoencoders can change facial expressions in photosBuild practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generationCreate recurrent generative models for text generation and learn how to improve the models using attentionUnderstand how generative models can help agents to accomplish tasks within a reinforcement learning settingExplore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

Jett's dad works at a coffee shop, and today Jett is going to work with him! Jett wants to do everything that he can to help his dad, but he just keeps messing up. Through Jett's silly blunders, he learns that what matters most at the coffee shop is how he makes people feel. In the end, Jett is proud that he is able to put a smile on people's faces.

The Scientific Angler. - Being a general and instructive work on artistic angling is an unchanged, high-quality reprint of the original edition of 1883.Hansebooks is editor of the literature on different topic areas such as research and science, travel and expeditions, cooking and nutrition, medicine, and other genres. As a publisher we focus on the preservation of historical literature. Many works of historical writers and scientists are available today as antiques only. Hansebooks newly publishes these books and contributes to the preservation of literature which has become rare and historical knowledge for the future.

"The Scientific Angler" is a vintage guide to fishing that takes a more scientific approach to the ancient sport and pastime than many other similar books. Including detailed explanations and expert tips, this profusely-illustrated volume will be of considerable utility to anglers new and old, and it would make for a fantastic addition to collections of related literature. Contents include: "The Habits and Haunts of Fish", "The Habits and Haunts of Fish (continued)", "Bottom Fishing", " Bottom Fishing (continued)", "Pike Fishing", "Spinning for Trout", "Worm Fishing for Trout", "Piscatorial Entomology", "On Fly Making", "Fly Fishing for Trout and Grayling", "Notes on the Months for Fly Fishing", "Salmon and Sea Trout Fishing", etc. Many vintage books such as this are becoming increasingly scarce and expensive. It is with that in mind that we are republishing this volume now in a modern, high-quality edition complete with a specially commissioned new introduction on the history of fishing.

Lassen Sie Ihre Deep-Learning-Modelle kreativ werden! Das Buch zeigt, wie die innovativsten Deep-Learning-Algorithmen wie Generative Adversarial Networks (GANs) und Variational Autoencoder (VAEs) funktionieren Für kreative Data Scientists und Programmierer, die gerne mit Code experimentieren Verwendet Python, Keras und TensorFlow Generative Modelle haben sich zu einem der spannendsten Themenbereiche der Künstlichen Intelligenz entwickelt: Mit generativem Deep Learning ist es inzwischen möglich, einer Maschine das Malen, Schreiben oder auch das Komponieren von Musik beizubringen - kreative Fähigkeiten, die bisher dem Menschen vorbehalten waren. Mit diesem praxisnahen Buch können Data Scientists einige der eindrucksvollsten generativen Deep-Learning-Modelle nachbilden, wie z.B. Generative Adversarial Networks (GANs), Variational Autoencoder (VAEs), Encoder-Decoder- sowie World-Modelle. David Foster vermittelt zunächst die Grundlagen des Deep Learning mit Keras und veranschaulicht die Funktionsweise jeder Methode, bevor er zu einigen der modernsten Algorithmen auf diesem Gebiet vorstößt. Die zahlreichen praktischen Beispiele und Tipps helfen Ihnen herauszufinden, wie Ihre Modelle noch effizienter lernen und noch kreativer werden können. Aus dem Inhalt Entdecken Sie, wie Variational Autoencoder den Gesichtsausdruck auf Fotos verändern können Erstellen Sie praktische GAN-Beispiele von Grund auf und nutzen Sie CycleGAN zur Stilübertragung und MuseGAN zum Generieren von Musik Verwenden Sie rekurrente generative Modelle, um Text zu erzeugen, und lernen Sie, wie Sie diese Modelle mit dem Attention-Mechanismus verbessern können Erfahren Sie, wie generatives Deep Learning Agenten dabei unterstützen kann, Aufgaben im Rahmen des Reinforcement Learning zu erfüllen Lernen Sie die Architektur von Transformern (BERT, GPT-2) und Bilderzeugungsmodellen wie ProGAN und StyleGAN kennen »Dieses Buch ist eine leicht zugängliche Einführung in das Deep-Learning-Toolkit für generatives Modellieren. Wenn Sie ein kreativer Praktiker sind, der es liebt, an Code zu basteln, und Deep Learning für eigene Aufgaben nutzen möchte, dann ist dieses Buch genau das Richtige für Sie.« - David Ha, Research Scientist bei Google Brain

Author, trainer, pastor, and radio talk show host David Foster urges readers to rip off the labels, libels, and limitations people have stuck on them and commit to a lifelong pursuit of excellence.

Monasteries and gaols: David Foster reflects that during the course of his life the monasteries have emptied while the gaols are doing nicely. Set in Goulburn and its surrounds, where Foster resides, The Contemptuary is a lament for a dying faith, a commentary on prison life and, perhaps unexpectedly from Foster in this, his sixteenth novel, an unputdownable whodunnit.'Attempt to characterise Foster's writing and eventually one will run out of adjectives. There is simply no one remotely like him in contemporary Australian fiction. He is so far ahead of everyone else that it's not funny.' - Australian Book Review