Python 面接の質問と回答

質問 101. What is monkey patching in Python?

Monkey patching is the term used to denote the modifications that are done to a class or a module during the runtime. This can only be done as Python supports changes in the behavior of the program while being executed.

質問 102. What is pandas?

Pandas is an open source python library which supports data structures for data based operations associated with data analyzing and data Manipulation. Pandas with its rich sets of features fits in every role of data operation,whether it be related to implementing different algorithms or for solving complex business problems. Pandas helps to deal with a number of files in performing certain operations on the data stored by files.

質問 103. What are dataframes?

A dataframe refers to a two dimensional mutable data structure or data aligned in the tabular form with labeled axes(rows and column).

• data:It refers to various forms like ndarray, series, map, lists, dict, constants and can take other DataFrame as Input.
• index:This argument is optional as the index for row labels will be automatically taken care of by pandas library.
• columns:This argument is optional as the index for column labels will be automatically taken care of by pandas library.
• Dtype: refers to the data type of each column.

質問 104. What is regression?

Regression is termed as supervised machine learning algorithm technique which is used to find the correlation between variables and help to predict the dependent variable(y) based upon the independent variable (x). It is mainly used for prediction, time series modeling, forecasting, and determining the causal-effect relationship between variables.

Scikit library is used in python to implement the regression and all machine learning algorithms.

There are two different types of regression algorithms in machine learning :

Linear Regression: Used when the variables are continuous and numeric in nature.

Logistic Regression: Used when the variables are continuous and categorical in nature.

質問 105. What is classification?

Classification refers to a predictive modeling process where a class label is predicted for a given example of input data. It helps categorize the provided input into a label that other observations with similar features have. For example, it can be used for classifying a mail whether it is spam or not, or for checking whether users will churn or not based on their behavior.

These are some of the classification algorithms used in Machine Learning:

• Decision tree
• Random forest classifier
• Support vector machine