Lecture 2 보충자료

[KimDahye]

cost function과 gradient decent 개념 (linear regression을 바탕으로), logistic regression의 cost function 설명 (아래는 Coursera의 Machine Learning by Andrew Ng 강의 동영상들의 일부입니다)

• Lecture 2.1 — Linear Regression With One Variable | Model Representation — Andrew Ng https://youtu.be/kHwlB_j7Hkc (8:10)
• Lecture 2.2 — Linear Regression With One Variable | CostFunction — Andrew Ng https://youtu.be/yuH4iRcggMw (8:12)
• Lecture 2.3 — Linear Regression With One Variable | Cost Function Intuition #1 | Andrew Ng https://youtu.be/yR2ipCoFvNo (11:09)
• Lecture 2.4 — Linear Regression With One Variable | Cost Function Intuition #2 | Andrew Ng https://youtu.be/0kns1gXLYg4 (8:48)
• Lecture 2.5 — Linear Regression With One Variable | Gradient Descent — [ Andrew Ng] https://youtu.be/F6GSRDoB-Cg (11:30)
• Lecture 2.6 — Linear Regression With One Variable | Gradient Descent Intuition — [ Andrew Ng] https://youtu.be/YovTqTY-PYY (11:51)

• Lecture 2.7 — Linear Regression With One Variable | Gradient Descent For Linear Regression https://youtu.be/GtSf2T6Co80 (10:20)

• Lecture 6.4 — Logistic Regression | Cost Function — [ Machine Learning | Andrew Ng] https://youtu.be/HIQlmHxI6-0 (11:25)

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참고. 위 영상들이 요약, 정리되어 있는 자료 (아래 자료 외에도 머신러닝 강의가 유명해서 다른 분들의 더 좋은 요약/정리 자료가 있을 수 있습니다)

• http://soopsaram.com/ml/markdowns/1.2-linear-regression-with-one-variable.html