Deep learning

Good text sharing

Ten predictions of 2019 year deep learning

Revolutionary progress should occur in stages, and what we are experiencing today is the main obstacle to achieving the Interventional level. This does not mean that we can't make any progress, but there are many unresolved results in the current maturity level, and these results are ready for development. The progress of DL in 2019 year will mainly focus on this pragmatic understanding.

Good text sharing

BAT expert interpretation: How to choose the most appropriate deep learning framework?

With deep learning attention and momentum, deep learning is being combined with the production practices of more and more companies and organizations. At this time, whether it is for beginners of deep learning related majors or developers who have been engaged in industrial scene application and R&D in enterprises and organizations, it is particularly important to choose a deep learning framework that suits their needs and suits the needs of business scenarios.

Good text sharing

Deep long text: a ten-year review of Chinese word segmentation

This paper reviews the technical progress of Chinese word segmentation in 2007-2017 for ten years, especially since the deep penetration of deep learning into natural language processing. Our basic conclusion is that the supervised machine learning method of Chinese word segmentation has not shown obvious technical advantages in the migration from non-neural network method to neural network method. The construction of the machine learning model of Chinese word segmentation still needs to balance the recognition problem of known words and unregistered words.

Chinese (Simplified) ZH-CN English EN