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  • Beautiful Soup
  • Dash by Plotly
  • Jupyter Notebook
  • Matplotlib
  • NLTK (Natural Language Toolkit)
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  • PyTorch
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  • SciPy
  • Seaborn
  • spaCy
  • TensorFlow

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  1. Disciplines

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Beautiful Soup

  • Description: A library for pulling data out of HTML and XML files.

  • Use Case: Used in educational data analysis for scraping educational resources, course contents, and learning materials from the web.

  • Documentation:

  • GitHub Repository:

Dash by Plotly

  • Description: A Python framework for building analytical web applications.

  • Use Case: Creating interactive web-based educational dashboards and learning tools.

  • Documentation:

  • GitHub Repository:

Jupyter Notebook

  • Description: An open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.

  • Use Case: Ideal for creating interactive educational content, tutorials, and live code demonstrations.

  • Documentation:

  • GitHub Repository:

Matplotlib

  • Description: A plotting library for creating static, animated, and interactive visualizations in Python.

  • Use Case: Generating plots and charts for educational materials, especially in STEM fields.

NLTK (Natural Language Toolkit)

  • Description: A leading platform for building Python programs to work with human language data.

  • Use Case: Used in language education and research for linguistic data analysis and natural language processing.

NumPy

  • Description: Fundamental package for scientific computing with Python.

  • Use Case: Handling numerical and mathematical computations in educational content, particularly in STEM subjects.

Pandas

  • Description: Data analysis and manipulation library.

  • Use Case: Data analysis and manipulation for educational research, student performance analysis, and educational data mining.

Plotly

  • Description: An interactive graphing library.

  • Use Case: Creating interactive educational visualizations and graphical representations of data.

PyTorch

  • Description: An open-source machine learning library.

  • Use Case: Developing machine learning models for educational purposes like personalized learning, prediction of student performance.

Scikit-learn

  • Description: Machine learning in Python.

  • Use Case: Implementing machine learning algorithms for educational data analysis, predictive modeling in education.

SciPy

  • Description: An open-source Python library used for scientific and technical computing.

  • Use Case: Technical computations in educational research and science education.

Seaborn

  • Description: A Python data visualization library based on Matplotlib.

  • Use Case: Creating informative and attractive statistical graphics for educational purposes.

spaCy

  • Description: An open-source software library for advanced natural language processing.

  • Use Case: Text analysis in education, such as processing educational texts, analyzing student feedback.

TensorFlow

  • Description: An open-source software library for machine learning applications.

  • Use Case: Developing educational models and simulations in areas such as personalized learning and educational games.

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Beautiful Soup Documentation
Beautiful Soup GitHub
Dash Documentation
Dash GitHub
Jupyter Documentation
Jupyter Notebook GitHub
Matplotlib Documentation
Matplotlib GitHub
NLTK Documentation
NLTK GitHub
NumPy Documentation
NumPy GitHub
Pandas Documentation
Pandas GitHub
Plotly Documentation
Plotly GitHub
PyTorch Documentation
PyTorch GitHub
Scikit-learn Documentation
Scikit-learn GitHub
SciPy Documentation
SciPy GitHub
Seaborn Documentation
Seaborn GitHub
spaCy Documentation
spaCy GitHub
TensorFlow Documentation
TensorFlow GitHub
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