今日爆单中，为了单车换摩托，拼了呀！
扫一扫又不会怀孕，扫一扫，作业无烦恼。
一日之计在于晨，最理想的状态就是工作+健身两不误，为了自己的事业和八块腹肌，尽情练起来吧！
选择rise锐泽paper咨询留学，那就跟您的作业coursework等等，好好告个别吧~毕竟很快就会pass这门课，统统加油呀！
加油呀！本节课需要阅读的三本书↓
- The Elements of Statistical Learning
- An introduction to statistical learning: With applications in R.
- Forecasting: principles and practice代写.
• Statistical terminologies are in bold or blue when first introduced, e.g., autoregression, recurrent neural network
• When there are something needed your attention, they are put in italic or red, e.g., This part will be tested in the exam
• This is an applied course – we focus more on applications, explaining how the methods work, how to use them, their advantages and limits, etc. Theoretical part and maths are also sometimes discussed briefly.
Predictive Analytics
Week 7: Advanced regression是最有意思的一个章节了
• We minimise the penalised RSS. The second terms penalises the parameter complexity
• It turns out that the idea of jointly optimising Error term + Model complexity term is very common in Statistics/Data Mining and Machine Learning
• Note that one usually doesn’t penalise the intercept β0
• λ controls the penalty, needs to be selected
