This massively comprehensive work of science fiction and fantasy bibliography is already a library standard. It consists of an alphabetical listing of hundreds of authors, anthologists, editors, artists, etc., with biographical sketches where available, and compilations of their science fiction and fantasy works. The contents of most collections and anthologies are listed. In most cases the entries include bibliographic data for all known English-language editions and forms, as well as some foreign translations. Each author's entry also includes listings of books and short stories which form connected series, such as Robert Heinlein's famous Future History. Large 8 1/2 x 11 inch pages in two columns of small print.

When a repairman accidentally discovers a parallel universe, everyone sees it as an opportunity, whether as a way to ease Earth's overcrowding, set up a personal kingdom, or hide an inconvenient mistress. But when a civilization is found already living there, the people on this side of the crack are sent scrambling to discover their motives. Will these parallel humans come in peace, or are they just as corrupt and ill-intentioned as the people of this world?

As a programmer for Galapagos Wetware, Hal Briggs is responsible for writing the genetic code for simple, efficient creatures to be employed in menial jobs–sweeping streets or washing dishes. But the demands for “wetware” are changing, and Briggs is given a project that calls for more sophisticated models: clients are demanding more human appearance and behavior. As the project progresses, Briggs finds himself endowing the new models with more than the specifications dictate, giving them distinct personalities and talents and highly developed acumens. When two of his pet projects, Jack and Kay, escape, Briggs reexamines their codes and makes a terrifying yet provocative discovery. From Craig Nova, a master of the modern novel, comes a tale eerie in its vision of a future not far off, of a world precariously close to today’s.

Well-known critic Brian Stableford, a former professor at the University of Reading, contributes "a fascinating and valuable attempt to grapple with the questions of why SF authors write what they write, and why SF readers like what they like"-Interzone. Contents: Introduction; Approaches to the Sociology of Literature; The Analysis of Communicative Functions; The Evolution of Science Fiction as a Publishing Category; The Expectations of the Science Fiction Reader; Themes and Trends in Science Fiction; and Conclusion: The Communicative Functions of Science Fiction. Complete with Notes and References, Bibliography, and Index.

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)