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: 2026-06-24 00:18:03 UTC
- JSON Representation
https://github.com/mauriciovazquezm/machinelearning_course_spring2023
Machine Learning course tasks focused on the implementation of the ML algorithms using libraries such as Numpy, Pandas, etc.
machine-learning machine-learning-algorithms numpy python r-language
Last synced: 05 May 2026
https://github.com/akash-rajak/image-resizer
Python Script to resize image to any dimension.
cv2 gui image-resizer numpy os python3 random resizeimage tkinter
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https://github.com/corentin-mzr/pmi
Project Master IPSA : Modeling the transport of a chemical species in a fluid
1d 2d fluid-dynamics fluid-simulation matplotlib numpy physics physics-2d physics-simulation python stochastic-processes
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https://github.com/guidorice/hab-detection-wyvern-hsi
Harmful Algal Bloom (HAB) Detection from Wyvern hyperspectral imagery
gdal geopandas gis hyperspectral jupyter numpy python rasterio
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https://github.com/nemeslaszlo/financial-crisis-effects-on-some-stocks
Focusing on bank stocks to see how they progressed throughout the 2008-09 financial crisis all the way to early 2016.
cufflinks jupyter-notebook matplotlib numpy pandas pandas-datareader plotly seaborn
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https://github.com/ahasannn/multilevel_textual_emotion_classifier
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matplotlib numpy pandas python seaborn statistics
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A VTO
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Examined factors influencing demand for micro-mobility shared electric cycles Performed exploratory analysis and hypothesis testing, revealing the distinct influence of weather-season association on hourly counts
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Determine which Whale portfolio is performing the best across multiple areas: volatility, returns, risk and Sharpe ratios.
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https://github.com/chandrasankarsaha-code/customer-churn-prediction
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cross-validation data-analysis data-preprocessing decision-trees gradient-boosting linear-regression machine-learning-algorithms numpy pandas random-forest regression scikit-learn
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matplotlib model numpy pickle python scikit-learn sklearn streamlit
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https://github.com/lohiyah/dataset_summariser
A Python tool for generating concise summaries of datasets using Pandas and NumPy for analysis, and Matplotlib and Seaborn for insightful visualizations. Ideal for quick exploratory data analysis (EDA).
matplotlib numpy pandas seaborn
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https://github.com/yenk/human-genomic-meta-analysis
Meta analysis of genomic studies to better understand if telomeres in the human genome are impacted by age from wild animals data.
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https://github.com/rayan-alam-uoit/space-x-launch-prediction-tool
A full-stack data science project analyzing SpaceX launch data using web scraping, REST APIs, SQL, interactive visualizations, and machine learning in Python to explore trends and predict launch success.
dash data-science folium jupyter-notebook machine-learning matplotlib numpy pandas plotly python seaborn sql sqlite
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https://github.com/mohitsai/boston-housing-data-analysis
Data Analysis Project for the City of Boston Government for insights into effect of property rennovations and remodelling on housing availability in the city
data-analysis data-science matplotlib numpy pandas python
Last synced: 05 May 2026
https://github.com/tapas-gope/diwali-sales-analysis
Analyze Diwali Sales Data to improve customer experience and sales.
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https://github.com/bearddan2000/python-web-3d-matplotlib-scatter-graph
A demo of creating a 3d scatter graph.
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https://github.com/anushkundu/crime-pattern-analysis
Analyzing Crime Patterns in Montgomery County, USA: An Inclusive Study Based on NIBRS Data (2016-2022)
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https://github.com/zuhairzia/customer-segmentation
📖 About Customer Segmentation using KMeans clustering to analyze demographics, income, and spending. Helps businesses with targeted marketing and customer insights.
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https://github.com/fayzi-dev/salary_predict_app_by_streamlit
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numpy pandas pypickle streamlit streamlit-webapp
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https://github.com/voidwalker7/mnist
MNIST Digit Detector Model using only Numpy
from-scratch-in-python mnist numpy python
Last synced: 05 May 2026
https://github.com/pramodyasahan/cifar-10-object-recognition
This repository contains a TensorFlow-based image classification model designed to classify images from the CIFAR-10 dataset. The CIFAR-10 dataset comprises 60,000 32x32 color images in 10 classes, with 6,000 images per class.
convolutional-neural-networks numpy python tensorflow
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https://github.com/anas436/generating-maps-with-folium-using-python
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https://github.com/nomissbowling/nomissbowling.github.io
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The Diwali sales analysis reviews past data to identify trends, peak buying times, popular products, and customer demographics. It assesses sales volume, revenue growth, and promotional effectiveness, helping businesses optimize marketing and inventory for future seasons.
data datacleaning eda excel jupyter-notebook matlplotlib numpy pandas python seaborn visualization
Last synced: 05 May 2026
https://github.com/nandinimarepalli/ai_ml_internship_projects
Projects completed during my AI/ML and Data Expert internship, including EDA, machine learning models, and dashboard development using Python, pandas, scikit-learn, and visualization libraries.
matplotlib numpy pandas python scikit-learn seaborn
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https://github.com/dulajkavinda/fashion-classification
👗 classify fashion items using machine learning
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https://github.com/ayushdutta-ai/face-recognition-model
A custom face recognition model built from scratch using Python, OpenCV, Pillow, and Face libraries, utilizing LBPH for efficient facial feature extraction and accurate identification.
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matplotlib ml numpy panda seaborn
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data-processing decision-tree-classifier machine-learning numpy pandas
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https://github.com/nkamilla/titanic-eda
Exploratory Data Analysis of the Titanic dataset using Python (Pandas, NumPy, Matplotlib). Includes data cleaning, visualizations, correlations, and key business insights.
data-analysis eda jupyter-notebook matplotlib numpy pandas python titanic-dataset
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https://github.com/kalwalt/pybind-test
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https://github.com/vikkiezdev/ai-global-index-analysis
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https://github.com/leavers/npblob
Transfer numpy array between Python and JavaScript losslessly
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https://github.com/shwetapardhi/assignment-1-q9_b--basic-statistics-level-1
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https://github.com/kashinathbiradar/bangalore-housing-price-prediction
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https://github.com/abdelrahman-amen/active_learning_with_different_query_strategies
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Python Plotting
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https://github.com/yashpaneliya/bank-loan-default-analysis
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Last synced: 06 May 2026
https://github.com/mat-kubiak/manual-ml
DIY ML framework (using only NumPy!) + various demos
artificial-intelligence examples machine-learning ml ml-framework neural-networks numpy
Last synced: 06 May 2026
https://github.com/sankaran-s2001/us-traffic-accidents-analysis-python-eda
Exploratory data analysis of US traffic accidents from 2016-2023, analyzing patterns by time, location, weather, and severity using Python data science libraries.
data-analysis data-science data-visualization eda matplolib numpy pandas python
Last synced: 06 May 2026
https://github.com/erick957/saleprice-prediction-dataset-analysis-and-cleaning-advance-regression
🏠 Predict house prices using advanced regression techniques with this comprehensive analysis and cleaning project, from data loading to model deployment.
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https://github.com/5hraddha/optimize-oil-well-locations
In the quest for harnessing valuable energy resources, the OilyGiant mining company wants to expand its operations by discovering new oil well locations. To achieve this, a data-driven approach is adopted, leveraging geological exploration data from three distinct regions and employing techniques in data analysis and modeling.
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https://github.com/prachi-77/data-visualization
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https://github.com/patilsukanya/assignment-05.-multiple-linear-regression-q2
Used libraries and functions as follows:
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