Conclusion, other advice, assignment and Recap

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Conclusion, other advice, assignment and Recap

  • In the case of this, try to split into training and test set and cros-validate to avoid over/underfitting

Kurt divide into qualitative and quantitative
  • Qualitative: Try to make better intuition, visualize, so we can better understanding the data, and ask a quality question to ask for our data. In doing so doing dimensionality reduction(PCA) to reduce dimension of data so we can better visualize it, so long in the clustering(K-means)
  • Quantitave: Not  just throwing a bunch of data, but rather selecting the features that causing the model, not based on instinct, but with analysis
Kurt's Advice
-Kurt's give 3 spesific fields, with particular interest
  1. Building Model. We like to model our system, data, for example recommender system. Then increase our coding skill,
  2. Data Analysis, increase statistical and machine learning, as well as mathematical analysis
  3. Communication, increase communication skill, subtract high-analysis data, and make conclusion to the company
  • It's important to know what our spesific interest among the three (or mixed) and increase the skill of particular field

  • Assignment is create t-test to know the subway rider, are more people into subway(raining/not raining/weekend)
  • We have talked about modeling existing data analysis, as well ass predicting the data in the future
  • We also have talked about statistic(Welch's t-test) and machine learning(linear regression)
  • Now we want to analyze and draw conlusion based on rider subway data
  • After that, we want to project our findings to family/friends. Doing so we will need data visualization