• This content is to share the following topics
  • Prerequisites on libraries
  • Load data & its definition
    • Some data manipulation with pandas
    • Slice on dataframe
    • Basic summary
    • Visualize & understande data with seaborn
  • Machine Learning
    • Decision Tree classifier with scikit-learn, graphviz, pydotplus
    • Logistic regression with scikit-learn
    • Deep Learning with keras, tensorflow
      • Equivalent to logistic regression
      • MLP -- adding layers
    • Compare accuracies for all models
  • Tips on execution
    • Save used memory with sparse model
    • Check process time with datetime, %%timeit
    • Parallel process with joblib (,cv2(opencv for python))
  • References

• The execution was confirmed with Python 3.6