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: 2026-06-25 00:18:02 UTC
- JSON Representation
https://github.com/bzubs/mlzero
Implementation of widely used ML algorithms in vanilla python
machine-learning machine-learning-algorithms machinelearning numpy python statistics
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https://github.com/dwija12903/ai-lab
A collection of practical implementations from my AI Labs course
keras numpy sckit-learn tensorflow
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https://github.com/octavioduarte/datascience
A repository with study notes on Data Science concepts, NumPy, pandas, and an introduction to statistics.
data-science jupyter-notebook numpy pandas
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A predictive maintainance model
decision-trees ipython matplotlib numpy pandas plotly python random-forest seaborn sklearn smote
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This is an basic application that uses Keras
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Image Enhancement with OpenCV Numpy and MatPlotLib
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https://github.com/dina-hosny/investigate-a-dataset-project
Investigate a Dataset project - Udacity Data Analysis Professional Track. In this project, I used the Python libraries NumPy, Pandas and Matplotlib to analyze a dataset and communicate my findings about it.
csv data-analysis jupyter-notebook matplotlib numpy pandas python
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https://github.com/pedasoft-consult/customer_analytics_fmcg
Customer Analytics in FMCG Industry
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https://github.com/iankitnegi/python_projects
Data Analyst Toolkit: A comprehensive collection of Python scripts and notebooks designed for data analysis tasks. Features data cleaning, visualization, statistical analysis, and machine learning models. Ideal for analysts seeking efficient, reproducible workflows.
matplotlib numpy pandas python seaborn
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https://github.com/niteshchawla/nc-walmart-casestudy
The Management team at Walmart Inc. wants to analyze the customer purchase behavior (specifically, purchase amount) against the customer’s gender and the various other factors to help the business make better decisions. They want to understand if the spending habits differ between male and female customers:.
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Linear Regression Algorithm
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https://github.com/rohansoni45/ipl-win-predictor
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https://github.com/gkamboj/image-features-extractor
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https://github.com/basith-ahmed/mtrp-butcher
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https://github.com/omcodewizard/nasa-battery-analysis
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IMT01306601-A Machine Learning
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https://github.com/ricobuilds/ml-roadmap
Opinionated roadmap to machine learning in 2023
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https://github.com/huzaifa12466/neuralnetscratch
A simple neural network implemented from scratch in Python using NumPy, trained on the Moons dataset
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https://github.com/radinshahdaei/ce40215-nc
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https://github.com/neerajcodes888/a-novel-used-car-price-prediction-model-based-on-lindenoise
Welcome to the LinDenoise Repository! LinDenoise offers a smart solution for cleaning noisy data in regression tasks. Integrated seamlessly within the widely-used scikit-learn framework, it effortlessly enhances data quality while improving predictive accuracy
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Breast Cancer Coimbra data set analysis
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https://github.com/psavarmattas/speechtotext
we shall build a very simple speech recognition system that takes our voice as input and produces the corresponding text by hearing the input.
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https://github.com/esraamhmd/intelligent-skin-cancer-image-based-detection-models
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https://github.com/amirmohammadgholampour/mall-customer-segmentation
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numpy pandas python scikit-learn
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https://github.com/satyas567/weatherdataanalysis
Comprehensive Weather Data Analysis with Python: Explore trends, visualize patterns, detect outliers, and predict temperature using humidity and wind speed
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https://github.com/lmizner/ece_c247_neuralnetworks
Course work from UCLA's ECE C247 - Neural Networks
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https://github.com/lmicovic/neural-network-image-recognition
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fashion-mnist keras machine-learning mathplotlib mnist-classification neural-network numpy opencv pandas python3 tensorflow
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https://github.com/bharath-tars/deeptumor2.0
DeepTumor2.0 is a project aimed at developing a flask webapp with robust front end and highly trained model using tensorflow in the backend with several features like with automatic html template reporting. **NOTE: DeepTumor2.0 has been moved from Azure to On-Render to save costs**
css datetime docs flask github html javascript keras numpy onrender os pandas python sheety smtp tensorflow
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https://github.com/davityak03/basics-of-python-
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array dictionary lists matrix numpy pandas programming python sets
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https://github.com/fairlytales/machine_learning
Workbooks for machine learning and neural network courses, textbooks, etc.
jupyter-notebook machine-learning machine-learning-algorithms matplotlib numpy opencv opencv-python pandas python pytorch scikit-learn scipy
Last synced: 14 Apr 2026
https://github.com/saylie/cat-dog-classifier-
The Cat-Dog Classifier is a deep learning-based image classification project that can differentiate between images of cats and dogs. It uses a Convolutional Neural Network (CNN) model trained on labeled datasets to predict whether a given image belongs to a cat or a dog.
ai javascript keras numpy opencv python react tensorflow
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https://github.com/niteshchawla/clustering-ml
Analyzing the vast data of learners can uncover patterns in their professional backgrounds and preferences. Allowing Scaler to make tailored content recommendations and provide specialized mentorship.
cluster-analysis clustering hierarchical-clustering k-means-clustering machine-learning numpy pca-analysis visualisation
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https://github.com/prajapatsur/data-analytics-1
Wanted to revise all the basic concepts of the data cleaning, transformation and analysis, so worked on this project. Took a little bit help of AI tool to implement some fresh concepts.
matplotlib numpy pandas sklearn
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https://github.com/ledsouza/curso_de_estatistica_parte_4
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data-science data-visualization numpy pandas seaborn statsmodels vitrinedev
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https://github.com/zohrabgulushev/data-science-with-python
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https://github.com/renan-siqueira/reinforcement-learning-cart-pole
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https://github.com/prashver/end-to-end-model-deployment-on-aws
Student Performance Analysis with Machine Learning analyzes factors impacting student outcomes using a robust machine learning pipeline. Achieving an impressive R2 score, it predicts student performance effectively. With extensive data preprocessing and deployment on AWS Elastic Beanstalk, it ensures scalability and high availability.
amazon-web-services aws-elastic-beanstalk end-to-end-deployment flask machine-learning-algorithms matplotlib numpy pandas scikit-learn seaborn
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https://github.com/arjunravi26/sentimental-analysis
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https://github.com/felixamaladhas/amazon-reviews-sentiment-analysis
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matplotlib numpy pandas python scikit-learn
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https://github.com/harmanveer2546/nasa-asteroid-classification
Classifying whether an asteroid is hazardous or not.
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https://github.com/tharushi11/titanic-data-analysis
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https://github.com/christiemj/clock-drift-simulation
A Monte Carlo simulation in Python to model vacuum-induced frequency drifts in atomic clocks, with code and visuals (experimental setup, simulated vs. real-world comparison, and drift graph), as described in "Probing Vacuum-Induced Clock Drifts via Quantum Metrology: A Testable Hypothesis" (DOI: 10.5281/zenodo.15163879). Licensed under GPL 3.0.
allan-variance atomic-clocks cesium-ion clock-drift matplotlib monte-carlo-simulation numpy open-science pandas physics precision-metrology python quantum-metrology research-software scipy simulation vacuum-fluctuations vacuum-noise
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https://github.com/filnow/tinygimp
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https://github.com/nikhilsree5/aerofitcasestudy
Customer Profiling and Market Segmentation for AeroFit Treadmills: A Data-Driven Approach
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Diabetes Prediction using futuristic tool
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https://github.com/khushi130404/binning-binarization
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Deep Learning Grid World Q-Learning . Implement Q-learning in a 5x5 grid where an agent navigates obstacles and rewards. Train the agent with varying learning rates, visualize its progress, and see Q-values as heatmaps. Run the script to start training and view results. Contributions are welcome!
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https://github.com/cbmira01/featureranking
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https://github.com/kaushik-puttaswamy/exploratory-data-analysis-using-python
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https://github.com/allanreda/automated-k-means-clustering-engine
An interactive K-Means clustering tool built with Flask and Scikit-Learn, supporting Excel file uploads, cluster analysis, and data export, deployed on Google Cloud Run via Docker with CI/CD integration.
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https://github.com/shhiivvaam/regression
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https://github.com/venkat-a/python-eda-exploratory-data-analysis-
This project focuses on conducting exploratory data analysis (EDA) using Python. Utilizing powerful libraries such as Pandas for data manipulation and Plotly for interactive visualization, the project aims to uncover insights from datasets through comprehensive analysis and visualization techniques.
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