Philip K. Dick Award finalist Praise for Vandana Singh: “A most promising and original young writer.”—Ursula K. Le Guin “Lovely! What a pleasure this book is . . . full of warmth, compassion, affection, high comedy and low.”—Molly Gloss, author of The Hearts of Horses “Vandana Singh’s radiant protagonist is a planet unto herself.”—Village Voice “Sweeping starscapes and daring cosmology that make Singh a worthy heir to Cordwainer Smith and Arthur C. Clarke.”—Chris Moriarty, Fantasy & Science Fiction “I’m looking forward to the collection . . . everything I’ve read has impressed me—the past and future visions in ‘Delhi’, the intensity of ‘Thirst’, the feeling of escape at the end of ‘The Tetrahedron’...” —Niall Harrison, Vector (British Science Fiction Association) “...the first writer of Indian origin to make a serious mark in the SF world ... she writes with such a beguiling touch of the strange.” —Nilanjana Roy, Business Standard In her first North American collection, Vandana Singh’s deep humanism interplays with her scientific background in stories that explore and celebrate this world and others and characters who are trying to make sense of the people they meet, what they see, and the challenges they face. An eleventh century poet wakes to find he is as an artificially intelligent companion on a starship. A woman of no account has the ability to look into the past. In "Requiem," a major new novella, a woman goes to Alaska to try and make sense of her aunt’s disappearance. Singh's stories have been performed on BBC radio, been finalists for the British SF Association award, selected for the Tiptree award honor list, and oft reprinted in Best of the Year anthologies. Her dives deep into the vast strangeness of the universe without and within and with her unblinking clear vision she explores the ways we move through space and time: together, yet always apart.

This tale is an unusual take on an engineering exam that explores new concepts in machine design and function. All new machine discoveries must be investigated and classified. This is the story of three such machines and the truth or lie of their existence. At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

The Nostalgist: A Tor.Com Original from Daniel H. Wilson. With EyesTM and EarsTM, everything can look and sound just fine, just like it used to be; it's a shock when they break down, though. This story has been adapted into a short film of the same name, directed by Giacomo Cimini and starring Lambert Wilson and Samuel Joslin. At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

This study draws from postcolonial theory, science fiction criticism, utopian studies, genre theory, Western and Indian philosophy and history to propose that Indian science fiction functions at the intersection of Indian and Western cultures. The author deploys a diachronic and comparative approach in examining the multilingual science fiction traditions of India to trace the overarching generic evolutions, which he complements with an analysis of specific patterns of hybridity in the genre’s formal and thematic elements – time, space, characters and the epistemologies that build the worlds in Indian science fiction. The work explores the larger patterns and connections visible despite the linguistic and cultural diversities of Indian science fiction traditions.

MACHINE OF DEATH tells thirty-four different stories about people who know how they will die. Prepare to have your tears jerked, your spine tingled, your funny bone tickled, your mind blown, your pulse quickened, or your heart warmed. Or better yet, simply prepare to be surprised. Because even when people do have perfect knowledge of the future, there's no telling exactly how things will turn out.

From author Charlie Jane Anders comes a Tor.com Original, Six Months, Three Days, winner of the Hugo Award for Best Novelette. Doug and Judy have both had a secret power all their life. Judy can see every possible future, branching out from each moment like infinite trees. Doug can also see the future, but for him, it's a single, locked-in, inexorable sequence of foreordained events. They can't both be right, but over and over again, they are. Obviously these are the last two people in the world who should date. So, naturally, they do At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Terry Bisson, author of the Hugo- and Nebula Award-winning short story "Bears Discover Fire," presents a Tor.Com Original, "The Cockroach Hat: A Literary Love Story." When Sam Gregory wakes up to find he has turned into a big cockroach, he is understandably dismayed. Luckily, the condition appears to be a little contagious. At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

A brilliant physicist attempts to salvage his planet of anarchy.

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.