Linear Ragression with multiple variables
Linear Ragression with multiple variables Multiple features Hypothesis: hθ(x)θ⃗ X⃗ =θT×X=[θ0,θ1,θ2⋯,θn]=[1,x1,x2⋯,xn] Gradient descent for multiple variables Hypothesis: hθ(x)=θT×X Parameters: θ
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相關文章
- 1. （2）Linear Regression with Multiple Variables
- 2. 機器學習2——Linear Regression with Multiple Variables
- 3. Machine Learning Andrew Ng -4. Linear Regression with multiple variables
- 4. ml-2-1-多變量線性迴歸( Linear Regression with Multiple Variables)
- 5. Stanford機器學習-Linear Regressioon with Multiple variables（1）
- 6. coursera機器學習公開課筆記4: linear-regression-with-multiple-variables
- 7. Linear Regression with multiple variables - Working on and submitting programming exercises
- 8. 四、多變量線性迴歸(Linear Regression with Multiple Variables)
- 9. 【Machine Learning】4 多變量線性迴歸(Linear Regression with Multiple Variables)
- 10. Linear Regression with multiple variables - Gradient descent in practice I: Feature Scaling