Deep learning
Applied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolution...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | كتاب |
| اللغة: | Undetermined |
| منشور في: |
Cambridge, Massachusetts
The MIT Press
[2016]
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://lrc.tdmu.edu.vn/opac/search/detail.asp?aID=2&ID=41713 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| Thư viện lưu trữ: | Trung tâm Học liệu Trường Đại học Thủ Dầu Một |
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| الملخص: | Applied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research. Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models. |
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| وصف مادي: | xxii, 775 pages |