Titlebook: Higher Education Computer Science; A Manual of Practica Jenny Carter,Michael O‘Grady,Clive Rosen Book 20181st edition Springer Nature Switz

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書目名稱Higher Education Computer Science影響因子(影響力)




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書目名稱Higher Education Computer Science網(wǎng)絡(luò)公開(kāi)度




書目名稱Higher Education Computer Science網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Higher Education Computer Science被引頻次




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書目名稱Higher Education Computer Science年度引用




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書目名稱Higher Education Computer Science讀者反饋




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GLOOM

cauda-equina

Liz Coulter-Smithe ontological difference between . and beings. This includes the deliberation on the difference between perception and observation, as well as that between actuality and reality. In short, this chapter is about the prospect of phenomenology in architectural scholarship.

不可思議

Diane Kitchinless modern people are ignorant, the consequences of their lifestyle on climate change will lead to self-destruction. To avoid this, this essay argues there is a necessity for rethinking our approach to planning/design and technology about the built environment. The purpose of this essay is retrospe

詞匯表

Michael O’Gradye ontological difference between . and beings. This includes the deliberation on the difference between perception and observation, as well as that between actuality and reality. In short, this chapter is about the prospect of phenomenology in architectural scholarship.

吝嗇性

Lice692

Thomas Lancasteriterate external formal and aesthetic qualities as they relate to pattern, color, proportion, hierarchy, and formal language. The human engagement in this design process is limited to the initial curation of input data in the form of image repositories of non-architectural disciplines that the machi

直覺(jué)沒(méi)有

veral times in order to record the preference. After being trained with the test result, the neural network can evaluate a new inputted form with a score from 0 to 1, indicating the predicted preference of the architect, showing the possibility of using machine learning to quantitatively evaluate pe

Precursor

Carlton McDonaldveral times in order to record the preference. After being trained with the test result, the neural network can evaluate a new inputted form with a score from 0 to 1, indicating the predicted preference of the architect, showing the possibility of using machine learning to quantitatively evaluate pe

涂掉

David Collinsiterate external formal and aesthetic qualities as they relate to pattern, color, proportion, hierarchy, and formal language. The human engagement in this design process is limited to the initial curation of input data in the form of image repositories of non-architectural disciplines that the machi