Machine learning algorithms usually operate as black boxes and it is unclear how they derived a certain decision. This book is a guide for practitioners on how to make machine learning decisions more interpretable.
Source: github.io
When both the AI and expert cardiologists were asked to classify the images, the AI achieved an accuracy of 92 percent. The humans got only 79 percent correct.
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Discover and seamlessly analyze open data
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At Google, we’re excited about the recent rapid progress of neural network-based text-to-speech (TTS) research. In particular, end-to-end architectures, such as the Tacotron systems we announced last year, can both simplify voice building pipelines and produce natural-sounding speech. This will help us build better human-computer interfaces, like conversational assistants, audiobook narration, news readers, or voice design software.
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