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AI Basic Tutorial Numpy+pandas+Matplotlib

This course mainly explains the basic library of Python scientific computing, array mathematical operation, multidimensional array construction, reshaping multidimensional array shape, and linear algebra. Load data, organize data, operate data, build data model, and analyze data. And data analysis data visualization.

three

Courses

three thousand eight hundred and sixty-five

Human learning

Total course duration

lisa

Lecturer rating: 5.0

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Systematic learning

Course content Q&A

Phase I: AI numpy basic database

1 course fifteen thousand nine hundred and sixty

As the foundation of data science, data partition machine learning and deep learning, numpy is very necessary to be consolidated.

Basic Tutorial of Artificial Intelligence Numpy
21 sections 4 hours and 26 minutes
Course objectives:
NumPy can process a large amount of data conveniently and efficiently. The advantages of data processing by NumPy are summarized as follows: NumPy is the basic library of Python scientific computing; NumPy can perform efficient mathematical operations on arrays; NumPy's array object can be used to build multidimensional arrays
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Phase II: Pandas data analysis

1 course sixteen thousand nine hundred and twenty

Enable students to master the data analysis and processing library pandas

Pandas data analysis
Section 29 4 hours 42 minutes
Course objectives:
The emergence of Pandas has greatly improved Python's ability to do data analysis. It mainly realizes five important links of data analysis: loading data, sorting data, operating data, building data models, and analyzing data. Pandas often conducts data analysis and processing, machine learning and deep learning
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Stage 3: Python data visualization - Matplotl

1 course seven thousand and two hundred

Learn the use of python's drawing toolkit matplotlib

Python Data Visualization - Maplotlib Tutorial
20 sections 2 hours
Course objectives:
Matplotlib is a very common drawing toolkit in python, which can be used to view and display the results of data analysis. This course focuses on: Visualize: use different kinds of charts to visualize the original data, making complex data easier to understand and use; Analysis (Ana
Course outline
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