| Abstrakt: |
With the development of artificial intelligence and the rapid development of machine learning in science and technology, deep learning is particularly important, especially in the fields of speech recognition and image recognition. Because the structure of the deep neural network is basically the same as that of the biological neural network in some features, the hidden feature information in the deep layer can be extracted efficiently and accurately, and the abstract attributes can be expressed objectively through learning. In terms of solving the fragmentation, new items, scalability, and other problems in the recommendation system, deep learning has its unique advantages. For example, when dealing with plain rainfall or personalized systems, system information can be analyzed, classified, and processed easily. Obtained extraordinary research results, which made the recommendation system solve the inherent problems in information analysis and ushered in new development opportunities. At the same time, French and English are both a common language, but there is a huge difference in the number of speakers. Although there are fewer French speakers than English speakers, French is grammatically strict is defined as the first language of the United Nations. With the development of globalization, French has become one of the common languages of international communication. In order to meet new challenges, strengthening French learning is a necessary way. In the end, this paper studies in the rainfall in the plains that the increase in Ca2+ content has a certain correlation with the rainfall in the plains. When the rainfall in the plain is less than 11.0 mm, the increase in the Ca2+ content is positively correlated with the rainfall, and the more rainfall, the increasing proportion of Ca2+ content is also higher; when the rainfall in the plain is higher than 11.0 mm, the increasing proportion of Ca2+ content is negatively correlated with rainfall. [ABSTRACT FROM AUTHOR] |
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