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/flexthink/matricize
A convenience library to convert between pure Python objects and their vectorized representations
data machine-learning numpy python
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https://github.com/ishaj72/analysis_model2
Dataset analysis model using matplotlib and other libraries
machine-learning matplotlib numpy pandas
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https://github.com/venkat-0706/titanic-survival-prediction
A machine learning project predicting Titanic passenger survival using data preprocessing, feature engineering, and model optimization with Logistic Regression, Random Forest, and XGBoost.
classification-report confusion-matrix gridsearchcv matplotlib numpy onehot-encoder pandas sckit-learn seaborn train-test-split xgboost
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https://github.com/brian-hepler-phd/kak-decomposition-qml
Cartan decomposition (SU(4)) via Lie theory and QML – exact + variational approaches for two-qubit gates.
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Data Analysis On Dr. Visits dataset
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https://github.com/nahiyanhkhan/data-processing-and-visualization
Loan Data Processing using Python's numpy and pandas libraries. For data visualization, matplotlib and seaborn are used.
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https://github.com/khaymanii/credit-card-fraud-detection-model
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algorithms machine-learning-algorithms matplotlib numpy pandas
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Contains self-implemented Machine Learning algorithms using only numpy.
boosting from-scratch knn learning logistic-regression machine ml numpy python random-forest regression sklearn testing xgboost
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https://github.com/abdullah2020/hamoye_stageb
This is my Hamoye Stage B project. The project focuses on Predicting Energy Efficiency of Buildings. It implemented different Machine Learning algorithm technique that are not limited to Linear Regression, LASSO, Ridge etc.
eda lasso-regression linear-regression numpy pandas predictive-modeling regression-models ridge-regression rmse rsquare-values
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https://github.com/carol-neto/sprint-4-statistical-data-analysis
In this project I had the opportunity to test my knowledge by analyzing a phone plan and creating graphs to compare the plans and determine which ones generate the most revenue.
matplotlib-pyplot numpy pandas pytho scipy-stats seaborn statistical-analysis
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Combining Machine Learning Techniques with Multi-Objective evolutionary Algorithms to Solve Real World Engineering Problems
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A simple Numpy & Python based auto differentiation system that supports visualization before and after back-propagation.
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Python reference code for data visualization, machine learning and SQL
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https://github.com/alphacrypto246/air-quality-prediction
The Air Pollution Prediction project forecasts pollution levels using the Air Quality UCI dataset, including variables like CO, NOx, temperature, and humidity. It analyzes temporal and environmental factors to predict air quality trends.
machine-learning numpy pandas scikitlearn-machine-learning sckiit-learn
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https://github.com/686f6c61/numeros-primos-gemelos
Este proyecto permite generar y visualizar números primos gemelos de diferentes formas para ayudar a comprender sus patrones y distribución. Incluye múltiples visualizaciones y análisis estadísticos avanzados.
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https://github.com/dawoudtormos/rain_predicition_ml
This repository contains a machine learning project for rain prediction using historical meteorological data. The goal is to predict whether it will rain the next day based on weather measurements like atmospheric water vapor, cloud formation, and past rainfall records.
ai machine-learning machine-learning-algorithms matplotlib numpy seaborn sklearn
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This project is an NLP-based Question-Answering System that leverages machine learning and natural language processing techniques to provide answers to user queries based on a given context or dataset. The system processes textual input, extracts meaningful insights, and returns relevant answers to the user's question.
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https://github.com/jupfu/beck-view-movie
Assemble mp4 video from list of images
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Many email services today provide spam filters that are able to classify emails into spam and non-spam email with high accuracy.
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https://github.com/mahmood-anaam/grid-world-value-iteration
An implementation of the Value Iteration algorithm for solving the Grid World problem. This project provides a function to compute the optimal value function for a grid-based environment where a robot navigates to maximize rewards while avoiding penalties.
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https://github.com/florasteve/ml-foundations-day2
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Efficient OMR software designed for quick and precise grading of bubble sheet exams.
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https://github.com/niteshchawla/loantap-logisticregression
Given a set of attributes for an Individual, determine if a credit line should be extended to them. If so, what should the repayment terms be in business recommendations?
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Hey! I am learning to build neural networks from scratch without the use of built-in Python libraries.
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https://github.com/shriansh2002/stock-prediction
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Notes about image processing
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Intelligent Python Performance Optimization Tool Automatically profile, analyze, and accelerate your Python code with minimal effort.
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https://github.com/shahriarha/programming
Python problem solving, HR-30 days of code, DSA, NumPy
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https://github.com/amirjahantab/deep-ml-solutions
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https://github.com/rishabhmathur06/fetching-jobs-data-using-beautifulsoup
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https://github.com/toxe/python-plotting
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https://github.com/yashpaneliya/bank-loan-default-analysis
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data-analysis loan-default-analysis matplotlib numpy pandas python
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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
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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
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https://github.com/swapnilvishwakarma/twitter_sentiment_dashboard
Using Streamlit and Python, I created interactive data dashboards and used Pandas to manipulate data in data science workflows. I also used Plotly to create interactive graphs.
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https://github.com/xanonymous-github/multimediax
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web content extraction and sentiment analysis on URLs provided in an Excel file. Its divided into classes to manage different stages such as data loading, web scraping, text processing, sentiment scoring, and output generation
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Last synced: 06 May 2026
https://github.com/sahilmate/gesturepainter
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https://github.com/fatihilhan42/lane-line-detection-with-python
In this project you will detect lane lines in images using Python and OpenCV. OpenCV means "Open-Source Computer Vision", which is a package that has many useful tools for analyzing images.
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https://github.com/bartosz-ziolkowski/social_data
Data analysis of San Francisco's crime data set from 2003 to 2018
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https://github.com/jayanthpotluri5513/heart-disease-prediction-using-ml
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