1. ML lec 00 - Machine/Deep learning

https://www.coursera.org/instructor/andrewng

 

강사 Andrew Ng | Coursera

Andrew Ng is Founder of DeepLearning.AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University. As a pioneer both in machine learning and online education, Dr. Ng has changed countless ...

www.coursera.org

http://www.holehouse.org/mlclass/

 

2. ML lec 01 - 기본적인 Machine Learning 의 용어와 개념 설명

1. Supervised learning : learning with labeled example

사람이 기계에서 'cat'이라는 라벨링 된 데이터를 준다.

 

2. Unsupervised learning : un-labeled data(ex. Google news grouping, Word clustering)

3. Traning data set

ML을 위해서는 label된 데이터 set이 있어야 하는데 왼쪽에 빨간색 친 데이터가 Training data set이다.

 

4. Types of supervised learning

  • Predicting final exam score based on time spent
    - regression
  • Pass/non-pass based on time spent
    - binary classification (둘 중 하나를 고르는 것)
  • Letter grade (A,B,C,E and F) based on time spend
    - multi-label classification (A,B,... label이 다양할 때 사용함)

 

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