인터넷, 데이터분석 링크. 2013/11/15

gist: https://gist.github.com/upepo/6408539

11/15

• Five Fundamental Concepts of Data Science
1. Begin with the end in mind!
• we should ask: What is the goal? What are we trying to achieve? How do we know if we are successful? If possible, we should quantify these end-goals with metrics – measurable outcomes, with some estimate of the “success threshold.”
2. Know your data!
3. Remember that this *is* science!
• we must remember that we are experimenting with data selections, data combinations, algorithms, combinations (ensembles) of algorithms, success metrics, accuracy measures, and more. All of these items should, at some point, be tested for their validity and applicability to the problem that you are trying to solve. We may know from past experience that a certain combination of data, features, and algorithms will satisfy our needs, but even that past experience was learned (not guessed). Remember this aphorism: “Good judgment comes from experience, and experience comes from bad judgment.”
4. Data are never perfect, but love your data anyway!
5. Overfitting is a sin against data science!
• 구글, 모든 책을 스캔할 수 있는 권리 획득
• Deep Learning 101
1. 딥러닝 101
• Scala documents
  • Programming in Scala, First Edition
  • Scalacheat
  • Scala Glossary
  • Stack Overflow ‘scala’ tag