We are in the process of writing a book on Mathematics for Machine Learning that motivates people to learn mathematical concepts. The book is not intended to cover advanced machine learning techniques because there are already plenty of books doing this. Instead, we aim to provide the necessary mathematical skills to read those other books.
Source: github.io
What if physiologists were the only people who study human behavior at all scales: from how the human body functions, to how social norms emerge, to how the stock market functions, to how we create, share, and consume culture? What if neuroscientists were the only people tasked with studying criminal behavior, designing educational curricula, and devising policies to fight tax evasion?
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Swift for TensorFlow is a result of first-principles thinking applied to machine learning frameworks, and works quite differently than existing TensorFlow language bindings. Whereas prior solutions are designed within the constraints of what can be achieved by a (typically Python or Lua) library, Swift for TensorFlow is based on the belief that machine learning is important enough to deserve first-class language and compiler support.
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NVIDIA’s Project Clara, a medical imaging supercomputer, renews the capabilities of these machines in place. Unveiled this week at the GPU Technology Conference, in Silicon Valley, Project Clara takes advantage of incredible advancements in computation.
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