Some methods of deep learning and dimensionality reduction
Deep Learning 上一篇主要是講了全鏈接神經網絡，這裏主要講的就是深度學習網絡的一些設計以及一些權值的設置。神經網絡能夠根據模型的層數，模型的複雜度和神經元的多少大體能夠分紅兩類：Shallow Neural Network和Deep Neural Network。比較一下二者：git Network Name Time complexity theoretical Shallow Ne
相關文章
- 1. Some methods of deep learning and dimensionality reduction
- 2. [UFLDL] Dimensionality Reduction
- 3. Paper Note --- Transfer Learning via Dimensionality Reduction
- 4. Nonlinear Dimensionality Reduction by Locally Linear Embedding
- 5. [Scikit-learn] 2.5 Dimensionality reduction - ICA
- 6. 壁虎書8 Dimensionality Reduction
- 7. What are some good books/papers for learning deep learning?
- 8. Dimensionality Reduction(降維)
- 9. 《A Review of Unsupervised Feature Learning and Deep Learning for Time-Series Modeling》筆記
- 10. CS231n Lecture 15 | Efficient Methods and Hardware for Deep Learning
- 更多相關文章...
- • XSLT
- • XSLT
- • RxJava操作符（七）Conditional and Boolean
- • Java Agent入門實戰（一）-Instrumentation介紹與使用
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Some methods of deep learning and dimensionality reduction
- 2. [UFLDL] Dimensionality Reduction
- 3. Paper Note --- Transfer Learning via Dimensionality Reduction
- 4. Nonlinear Dimensionality Reduction by Locally Linear Embedding
- 5. [Scikit-learn] 2.5 Dimensionality reduction - ICA
- 6. 壁虎書8 Dimensionality Reduction
- 7. What are some good books/papers for learning deep learning?
- 8. Dimensionality Reduction(降維)
- 9. 《A Review of Unsupervised Feature Learning and Deep Learning for Time-Series Modeling》筆記
- 10. CS231n Lecture 15 | Efficient Methods and Hardware for Deep Learning