What do you need to learn about python data mining?

As long as it can solve practical problems, it doesn’t matter what tool you use to learn data mining. Python is the first choice here.

What knowledge do you need to master in Python?(Recommended learning: Python video tutorial)

1. Operation of Pandas library

Panda is a particularly important library for data analysis. We must master the following three points:

· pandas group calculation;

· pandas index and multiple index;

Index is difficult, but it is very important

· pandas multi-table operation and pivot table

2, numpy numerical calculation

The main application of numpy data calculation is in data mining. For future machine learning and deep learning, this is also a library that must be mastered. We must master the following contents:

· Numpy array understanding;

· Array index operation;

· Array calculation;

· Broadcasting (knowledge in linear algebra)

3. Data visualization-matplotlib and seaborn

· Matplotib syntax

The most basic visualization tool for python is matplotlib. At first glance, Matplotlib and matlib look a bit similar. You need to understand the relationship between the two, so that it will be easier to learn.

·Using seaborn

seaborn is a very beautiful visualization tool.

· pandas drawing function

As mentioned before, pandas is used for data analysis, but it also provides some drawing APIs.

4. Introduction to data mining

This part is the most difficult and interesting part. You must master the following parts:

·Machine learning The definition of

will not be different from data mining here

· The definition of cost function

· Train/Test/Validate

· The definition of Overfitting And avoidance methods

5. Data mining algorithms

With the development of data mining, there are many algorithms. Below we only need to master the simplest, most core and most important ones. Commonly used algorithms:

· Least squares algorithm;

· Gradient descent;

· Vectorization;

· Maximum likelihood estimation;

·Logistic Regression;

·Decision Tree;

·RandomForesr;

·XGBoost;

6. Data Mining Practical combat

Use scikit-learn, the most famous library in machine learning, to understand the model.

For more Python related technical articles, please visit the Python Tutorial column to learn!

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