NumPy
NumPy is an open source library for the Python programming language, adding support for large, multidimensional arrays, and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
- GitHub: https://github.com/topics/numpy
- Wikipedia: https://en.wikipedia.org/wiki/NumPy
- Repo: https://github.com/numpy/numpy
- Created by: Travis Oliphant
- Related Topics: python, scipy,
- Last updated: 2026-06-26 00:18:09 UTC
- JSON Representation
https://github.com/onemoredavid/python-like-a-boss
This is where I stash my Python study material.
data data-analysis data-engineering data-science data-visualization datascience ipynb ipynb-jupyter-notebook ipynb-notebook numpy pandas python python3
Last synced: 04 Apr 2025
https://github.com/haydencordeiro/terafeed
Terafeed - Addressing Zero Hunger in Africa (Sustainability Goal SDG 2)
javscript numpy pandas powerbi python scikit-learn tableau vuejs
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https://github.com/azaz9026/data_cleaning
Welcome to the Data Cleaning repository! This collection is dedicated to showcasing techniques and methods for cleaning and preparing datasets for analysis.
data-analysis data-engineering data-structures data-visualization eda feature-engineering machine-learning numpy outliers pandas python seaborn
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https://github.com/chandkund/image-classification-using-the-mnist-dataset
Image Classification using the MNIST dataset. This project leverages a Convolutional Neural Network (CNN) to recognize and classify handwritten digits with high accuracy. Includes data preprocessing, model architecture, and evaluation. Explore the code and results here!
computer-vision data-science machine-learning matplotlib numpy pandas python
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https://github.com/allanreda/telco-customer-churn-predictor-app
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app-engine data-visualization deployment google-cloud gradio hyperparameter-tuning logistic-regression machine-learning numpy pandas scikit-learn
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jupyter-notebook numpy pandas python3
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Workspace for Neural Networks class
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eda jupyter-notebook mongodb numpy pandas powerbi preprocessing
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Some useful np.random functions
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