Key Information
About the content
The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。]
Syllabus
Embedding Numerous Features [嵌入大量的特徵]
-- Linear Support Vector Machine [線性支持向量機]
-- Dual Support Vector Machine [對偶支持向量機]
-- Kernel Support Vector Machine [核型支持向量機]
-- Soft-Margin Support Vector Machine [軟式支持向量機]
-- Kernel Logistic Regression [核型羅吉斯迴歸]
-- Support Vector Regression [支持向量迴歸]
Combining Predictive Features [融合預測性的特徵]
-- Bootstrap Aggregation [自助聚合法]
-- Adaptive Boosting [漸次提昇法]
-- Decision Tree [決策樹]
-- Random Forest [隨機森林]
-- Gradient Boosted Decision Tree [梯度提昇決策樹]
Distilling Hidden Features [萃取隱藏的特徵]
-- Neural Network [類神經網路]
-- Deep Learning [深度學習]
-- Radial Basis Function Network [逕向基函數網路]
-- Matrix Factorization [矩陣分解]
Summary [總結]
Instructors
- Hsuan-Tien Lin - 資訊工程學系 (Computer Science and Information Engineering)
Content Designer
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
