Machine Learning: Class Two: Regression
Regression: Output a scalar 1.Application 2.An Example step 1: Model Model: a set of function W and B are parameters（因數）, W(i): weight（權重）, B(i): bias（偏移量） X(i) are the features（特性） step 2: the Goodne
相關文章
- 1. Machine Learning - Logistic Regression - Two-class Classification
- 2. Machine Learning in Action (5) —— logistic regression
- 3. Machine learning(4):Linear regression
- 4. [Machine Learning] 迴歸（Regression）
- 5. 【Machine Learning】Machine Learning 綜述
- 6. Machine Learning Kaggle Competition Part Two
- 7. Machine Learning Andrew Ng -6. Logistic Regression
- 8. Machine Learning—Classification and logistic regression
- 9. Machine Learning Series No.2 --Logistic Regression
- 10. Coursera Machine Learning Week 6 - Advice for Applying Machine Learning
- 更多相關文章...
- • Docker Machine - Docker教程
- • C# 類（Class） - C#教程
- • Java Agent入門實戰（一）-Instrumentation介紹與使用
- • Java Agent入門實戰（三）-JVM Attach原理與使用
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。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Machine Learning - Logistic Regression - Two-class Classification
- 2. Machine Learning in Action (5) —— logistic regression
- 3. Machine learning(4):Linear regression
- 4. [Machine Learning] 迴歸（Regression）
- 5. 【Machine Learning】Machine Learning 綜述
- 6. Machine Learning Kaggle Competition Part Two
- 7. Machine Learning Andrew Ng -6. Logistic Regression
- 8. Machine Learning—Classification and logistic regression
- 9. Machine Learning Series No.2 --Logistic Regression
- 10. Coursera Machine Learning Week 6 - Advice for Applying Machine Learning