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The Book of Shaders
A gentle step-by-step guide through the abstract and complex universe of Fragment Shaders
book  graphics  programming  tutorial  shaders  3d  glsl  opengl 
yesterday by deveiant
Religious networks roman empire spread new ideas | Ancient history | Cambridge University Press
The first three centuries AD saw the spread of new religious ideas through the Roman Empire, crossing a vast and diverse geographical, social and cultural space. In this innovative study, Anna Collar explores both how this happened and why. Drawing on research in the sociology and anthropology of religion, physics and computer science, Collar explores the relationship between social networks and religious transmission to explore why some religious movements succeed, while others, seemingly equally successful at a certain time, ultimately fail. Using extensive epigraphic data, Collar provides new interpretations of the diffusion of ideas across the social networks of the Jewish Diaspora and the cults of Jupiter Dolichenus and Theos Hypsistos, and in turn offers important reappraisals of the spread of religious innovations in the Roman Empire. This study will be a valuable resource for students and scholars of ancient history, archaeology, ancient religion and network theory.
book  archaelogy  history_of_ideas  epidemiology_of_representations  religion  social_networks  ?  teaching  networks  via:cass.sunstein 
yesterday by rvenkat
How to Successfully Get Your Book on the Market
Authors now have even more routes to the bestseller list. But before the fame and fortune, the book has to make it onto the market first.
book  books  book-marketing 
yesterday by Adventure_Web
Hands-On Machine Learning with Scikit-Learn and TensorFlow - O'Reilly Media
Explore the machine learning landscape, particularly neural nets
Use scikit-learn to track an example machine-learning project end-to-end
Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
Use the TensorFlow library to build and train neural nets
Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
Learn techniques for training and scaling deep neural nets
Apply practical code examples without acquiring excessive machine learning theory or algorithm details
book  Python  ai 
yesterday by janpeuker

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