Build an image classifier (ML Zero to Hero - Part 4)
common.language.envideo.subtitles common.language.native.short.vi, common.language.native.short.ko, common.language.native.short.zh-TW, common.language.native.short.ja, common.language.native.short.id, common.language.native.short.zh-CN
In part four of Machine Learning Zero to Hero, AI Advocate Laurence Moroney ([email protected]) discusses the build of an image classifier for rock, paper, and scissors. In episode one, we showed a scenario of rock, paper, and scissors; and discussed how difficult it might be to write code to detect and classify these. As the episodes have progressed into machine learning, we’ve learned how to build neural networks from detecting patterns in raw pixels, to classifying them, to detecting features using convolutions. In this episode, we have put all the information from the first three parts of the series into one.
Colab notebook →http://bit.ly/2lXXdw5
Rock, paper, scissors dataset → http://bit.ly/2kbV92O
This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish.
Watch more Coding TensorFlow → http://bit.ly/2lytA4j
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