AI and Efficiency. 25 ML Best Practices. Data Quality @ Uber. Beekeeper. The Fragility of ML. [DSR #226]
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❤️ Want to support this project? Forward this email to three friends! 🚀 Forwarded this from a friend? Sign up to the Data Science Roundup here. This week's best data science articles AI and Efficiency We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet (by contrast, Moore’s Law would yield an 11x cost improvement over this period). Our results suggest that
AI and Efficiency. 25 ML Best Practices. Data Quality @ Uber. Beekeeper. The Fragility of ML. [DSR #226]
AI and Efficiency. 25 ML Best Practices. Data…
AI and Efficiency. 25 ML Best Practices. Data Quality @ Uber. Beekeeper. The Fragility of ML. [DSR #226]
❤️ Want to support this project? Forward this email to three friends! 🚀 Forwarded this from a friend? Sign up to the Data Science Roundup here. This week's best data science articles AI and Efficiency We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet (by contrast, Moore’s Law would yield an 11x cost improvement over this period). Our results suggest that