With the advent of the era of big data, the amount of information shows an exponential explosive growth trend. At the same time, the personalized needs of users are increasing. Facing the massive data, how to help users quickly and accurately obtain the information they need is the main challenge facing them at present. With the rapid development of computer technology and communication technology, mobile teaching and deep learning have become new research hotspots in the field of education. Mobile education has become a very fashionable education mode, which not only brings modern people a more convenient education system, but also makes modern learners need not worry about learning time and content. Traditional recommendation methods generally have problems such as sparse data, cold start and difficulty in feature extraction. On the basis of expounding the concept, connotation and main characteristics of deep learning, this paper applies deep learning theory to mobile recommendation system, hoping to gradually improve and promote the existing mobile education and provide an effective learning way and method for learners.
Computer Science and technology are following the wheels of social development, constantly moving forward, and epoch-making artificial intelligence technology has emerged. As soon as artificial intelligence technology appeared, it quickly became popular in all industries. After applying artificial intelligence technology to the Internet, society’s demand for artificial intelligence has reached a peak.
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