第25月第8天 100-Days-Of-ML-Code

1.100-Days-Of-ML-Code

 

 

2.practical-machine-learning-with-python

3.ud120

Intro to ML (Udacity) ​

 

sklearn 0.20.0 代码运行问题

/tools/email_preprocess.py

from sklearn import cross_validation

改为 from sklearn.model_selection import train_test_split

 

 4.ud501

 

Lesson outline

In this lesson you will learn how to read data, select subsets of it and generate useful plots, using ​​pandas​​ and ​​matplotlib​​. The documentation links below are for your reference.

• Read stock data from CSV files:

• Select desired rows and columns:

• ​​Indexing and Slicing Data​​
• Gotchas: ​​Label-based slicing conventions​​

• Visualize data by generating plots:

 

Lesson outline

Here's an overview of what you'll learn to do in this lesson. Documentation links are for reference.

Read in multiple stocks:

• Create an empty ​​pandas.DataFrame​​ with dates as index: ​​pandas.date_range​​
• Drop missing date rows: ​​pandas.DataFrame.dropna​​
• Incrementally join data for each stock: ​​pandas.DataFrame.join​​

Manipulate stock data:

• ​​Index and select data​​ by row (dates) and column (symbols)
• Plot multiple stocks at once (still using ​​pandas.DataFrame.plot​​)
• Carry out arithmetic operations across stocks
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