| 词汇 | deep-learning |
| 释义 | deep learning noun[ U ] uk /ˌdiːp ˈlɜː.nɪŋ/ us /ˌdiːp ˈlɝː.nɪŋ/ education specialized a complete way of learning something that means you fully understand it and will not forget it: 深度学习 Deep learning is the kind you take with you through the rest of your life.深度学习是一种终身伴随你的学习。 computing specialized a type of machine learning (= the process of computers improving their own ability to perform tasks by analysing new data) that uses many layers of data processing: Deep learning has been responsible for the most exciting developments in data science in recent years. Face identification tasks can now be solved by deep learning. Kolb asserted that deep learning comes through a sequence of experience, reflection, abstraction, and active testing. There remains a flawed assumption that deep learning can be acquired and assessed in conveniently bite-size chunks. Research showed that those with a deep learning style were likely to organise ideas into networks. Deep learning has powerful implications for machine translation. Many search engines use deep learning to optimize results. Learning & knowing absorptive capacity achievement gap acquirable acquire acquisition bone hit the booksidiom know better (than to do something)idiom know something from something know something like the back of your handidiom know your way around somethingidiom language acquisition orientation recognition recognize study under someone subskill subspeciality subspecialize subspecialty You can also find related words, phrases, and synonyms in the topics: Computer concepts Examples of deep learningdeep learning Deeplearning in musikdidaktik required a level of experience with trainees' musical instrument, which was usually developed during the first year at the institution. Deeplearning was enhanced by the sequencing and integration of musikdidaktik, principal instrument and practical teacher training. Hence, the possibilities for enhancing deeplearning in musikdidaktik also seemed embedded outside the subject, yet within the institutional culture itself. One important interest in this school is the relationship between deeplearning and valued language in academic disciplines. The preconditions for deeplearning that were identified as located to the trainees included the areas of trainee identity, learning orientations and musical experience. The position of the musikdidaktik subject within music teacher education as a whole was also perceived to influence the possibility of deeplearning. The preconditions that were perceived as significant for deeplearning included professors' attitudes to the trainees' preconditions and professors' approaches to the subject. The interviewees particularly emphasised the institution's disposition towards time allocation, and its organisation as being significant for the trainees' deeplearning. It was held that trainee preconditions for deeplearning in musikdidaktik were strongly related to trainees' musical maturity. Summing up, three issues that could be connected to the professors emerged as significant for trainees to achieve deeplearning. Summing up, three time-related issues emerged as significant for the trainees' deeplearning. The professor-content relation of the didaktik triangle was perceived to include preconditions for the trainees' deeplearning in several significant ways. Summing up, five issues that concerned the institutions' educational organisation emerged as significant for the trainees' deeplearning. Another, institutional precondition that seemed to influence trainees' deeplearning rather strongly were the relations between the musikdidaktik subject and practical teacher training. This made it impossible for trainees to achieve deeplearning in all subjects. See all examples of deep learning These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. |
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