• 2017 World Fantasy Award finalist for Best Anthology • Contains “The Fall Shall Further the Flight in Me” by Rachael K. Jones, 2017 World Fantasy Award finalist for Best Short Fiction • Contains “Sabbath Wine” by Barbara Krasnoff, 2016 Nebula Award finalist for Best Short Story • 2016 Locus Recommended Reading List, Best Anthology “Allen’s strange and lovely fifth genre-melding fantasy anthology selects 20 new short stories of unusual variety, texture, compassion, and perception. . . . All the stories afford thought-provoking glimpses into alternative realities that linger, sparking unconventional thoughts, long after they are first encountered.” —Publishers Weekly, starred review “The arrangement is superb. This anthology of 20 stories can resemble a symphony of themes and variations in a wide range of keys, or a tapestry whose elements form patterns of imagery and meaning that shift and offer new insights throughout the book.” —Locus The Clockwork Phoenix anthologies offer homes to “well-written stories occupying multiple subgenres, usually in the same story, often ambiguously,” as Locus Magazine once put it. The ground-breaking, boundary-pushing, award-nominated series has returned for a fifth incarnation, triumphantly risen from the ashes after another successful Kickstarter campaign. This is the largest installment yet, holding twenty new tales of beauty and strangeness. With original fiction from Jason Kimble, Rachael K. Jones, Patricia Russo, Marie Brennan, Benjanun Sriduangkaew, Rob Cameron, A. C. Wise, Gray Rinehart, Sam Fleming, Sunil Patel, C. S. E. Cooney and Carlos Hernandez, Holly Heisey, Barbara Krasnoff, Sonya Taaffe, Alex Dally MacFarlane, Shveta Thakrar, Cassandra Khaw, Keffy R. M. Kehrli, Rich Larson, and Beth Cato. Cover art by Paula Arwen Owen. “And then there is that secret restaurant . . . It is perfection on a plate! And you feel better about yourself and your life and the world every time you go there. Clockwork Phoenix is the name of this restaurant, and Mike Allen is the restaurateur. One sublime dish after another, and yet I still have my favorites that I keep coming back to.” —Little Red Reviewer Table of contents: “The Wind at His Back” by Jason Kimble “The Fall Shall Further the Flight in Me” by Rachael K. Jones “The Perfect Happy Family” by Patricia Russo “The Mirror-City” by Marie Brennan “The Finch’s Wedding and the Hive That Sings” by Benjanun Sriduangkaew “Squeeze” by Rob Cameron “A Guide to Birds by Song (After Death)” by A.C. Wise “The Sorcerer of Etah” by Gray Rinehart “The Prime Importance of a Happy Number” by Sam Fleming “Social Visiting” by Sunil Patel “The Book of May” by C.S.E. Cooney and Carlos Hernandez “The Tiger’s Silent Roar” by Holly Heisey “Sabbath Wine” by Barbara Krasnoff “The Trinitite Golem” by Sonya Taaffe “Two Bright Venuses” by Alex Dally MacFarlane “By Thread of Night and Starlight Needle” by Shveta Thakrar “The Games We Play” by Cassandra Khaw “The Road, and the Valley, and the Beasts” by Keffy R.M. Kehrli “Innumerable Glimmering Lights” by Rich Larson “The Souls of Horses” by Beth Cato

Is there a better phrase to start a story than "No Shit, There I Was..."? If you hear someone start with that phrase, you know it's going to be worth listening carefully. That's how all the craziest - and most interesting - stories start. And then we turned a bunch of speculative fiction authors loose on that phrase.

This book is the out come from the personnel's who have their foot in microbiology science last two decades. It's a collection of almost a dozen of sister concerned disciplines in microbiology. It includes more than 6900 terms related to microbiology. This book will become and essential book to all who have some bearing with microbiology and fields like mycology, bacteriology, virology, microbe-biotechnology, parasitology etc.

Learn how to redesign NLP applications from scratch. KEY FEATURESÊÊ ¥ Get familiar with the basics of any Machine Learning or Deep Learning application. ¥ Understand how does preprocessing work in NLP pipeline. ¥ Use simple PyTorch snippets to create basic building blocks of the network commonly used inÊ NLP.Ê ¥ Learn how to build a complex NLP application. ¥ Get familiar with the advanced embedding technique, Generative network, and Audio signal processing techniques. ÊÊ DESCRIPTIONÊ Natural language processing (NLP) is one of the areas where many Machine Learning and Deep Learning techniques are applied. This book covers wide areas, including the fundamentals of Machine Learning, Understanding and optimizing Hyperparameters, Convolution Neural Networks (CNN), and Recurrent Neural Networks (RNN). This book not only covers the classical concept of text processing but also shares the recent advancements. This book will empower users in designing networks with the least computational and time complexity. This book not only covers basics of Natural Language Processing but also helps in deciphering the logic behind advanced concepts/architecture such as Batch Normalization, Position Embedding, DenseNet, Attention Mechanism, Highway Networks, Transformer models and Siamese Networks. This book also covers recent advancements such as ELMo-BiLM, SkipThought, and Bert. This book also covers practical implementation with step by step explanation of deep learning techniques in Topic Modelling, Text Generation, Named Entity Recognition, Text Summarization, and Language Translation. In addition to this, very advanced and open to research topics such as Generative Adversarial Network and Speech Processing are also covered. WHAT YOU WILL LEARNÊ ¥ Learn how to leveraging GPU for Deep Learning ¥ Learn how to use complex embedding models such as BERT ¥ Get familiar with the common NLP applications. ¥ Learn how to use GANs in NLP ¥ Learn how to process Speech data and implementing it in Speech applications Ê WHO THIS BOOK IS FORÊ This book is a must-read to everyone who wishes to start the career with Machine learning and Deep Learning. This book is also for those who want to use GPU for developing Deep Learning applications. TABLE OF CONTENTSÊÊ 1. Understanding the basics of learning Process 2. Text Processing Techniques 3. Representing Language Mathematically 4. Using RNN for NLP 5. Applying CNN In NLP Tasks 6. Accelerating NLP with Advanced Embeddings 7. Applying Deep Learning to NLP tasks 8. Application of Complex Architectures in NLP 9. Understanding Generative Networks 10. Techniques of Speech Processing 11. The Road Ahead