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/sahraiidle/email-spam-detector
Email/SMS spam detector with a Flask UI/API, tuned ML models (TF‑IDF + SVM/LogReg/NB), and a ready-to-run web form plus JSON endpoint for predictions.
data machine-learning numpy pandas python randomforest scikit-learn spam-classifier spam-detection svm
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https://github.com/dilkushsingh/iris-species-classifier
Used Random Forest Classifier Algorithm
huggingface-spaces numpy pandas python random-forest-classifier scikit-learn streamlit
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https://github.com/jaybfn/single-molecule-electrophysiology-data-analysis
Pynanopore serves as a sophisticated toolkit for analyzing single molecules, designed to interpret complex states within nanopore data automatically.
docker numpy pandas plotly pytest python3 streamlit streamlit-webapp
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https://github.com/shwetapardhi/assignment-03-q5--hypothesis-testing
Chi2 contengency independence test Q5. Fantaloons Sales managers commented that % of males versus females walking in to the store differ based on day of the week. Analyze the data and determine whether there is evidence at 5 % significance level to support this hypothesis. Assume Null Hypothesis as Ho: Independence of categorical variables (% of
alternate-hypothesis chi2-contingency contingency-analysis hypothesis-testing null-hypothesis numpy pandas python scipy significance-testing stats
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matplotlib numpy pid-controller python scypi streamlit
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https://github.com/shahaba83/airplane-ticket-cancellation
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https://github.com/deepankkartikey/ml-projects
A repository of projects done while learning and exploring ML
classification csv machine-learning numpy pandas regression sklearn
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The utilization of the ResNet architecture and Transfer Learning methods to classify Poultry Meat Freshness images into two categories, namely Fresh and Rotten.
artificial-intelligence binary-classification cnn colab-notebooks computer-vision deep-learning fine-tuning imagenet machine-learning meat-classification numpy pandas poultry python residual-networks resnet scikit-learn supervised-learning tensorflow transfer-learning
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https://github.com/ljadhav25/decision-tree-random-forest-algorithm-data-science-
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https://github.com/itssahilwhat/ai-fundamentals
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https://github.com/manu-karenite/medical-insurance-cost-predictor
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https://github.com/breadrock1/ml-labs
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https://github.com/codehub001/age-and-gender-detection
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https://github.com/chandkund/sentiment-analysis-on-movie-reviews
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https://github.com/nits2612/data-science-projects
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https://github.com/rissh/titanicsurvivalpredictionusingml
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https://github.com/murugavl/forage_tata_genai_powered_data_analytics
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https://github.com/nagar2nd/ml-regressionmodel---cardekho-price-prediction
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all about machine learning
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https://github.com/hygull/trypandas
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https://github.com/urvee1810/air-quality-prediction-using-arima
Analyzed Beijing's air quality data using time series analysis and ARIMA modeling to forecast PM2.5 pollution levels. Identified seasonal patterns and correlations between pollutants, revealing insights into urban air quality trends and potential contributing factors.
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https://github.com/magnusrodseth/disaster-tweets
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https://github.com/bzubs/mlzero
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Last synced: 01 Apr 2026
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https://github.com/oguzhantekeli06/datascience_machinelearning_prediction
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https://github.com/kganitis/bam-engine
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https://github.com/jay6430/python-for-data-science
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https://github.com/supershivam5/python_projects
💻 Python programming with Numpy, Pandas, Matplotlib.🌟 Love exploring new technologies. Check out my projects!
matplotlib-pyplot numpy pandas scikit-learn seaborn
Last synced: 17 Apr 2026
https://github.com/syedzaheerabbas/risk-analytics-with-python
This project focuses on developing a basic understanding of risk analytics in banking and financial services and understand how data is used to minimize the risk of losing money while lending to customers.
eda hypothesis-testing numpy pandas python risk-analysis seaborn
Last synced: 17 Apr 2026
https://github.com/vaishnavis03/finlatics_ml_program
This repository contains the .ipynb files for 3 datasets, along with a PPT for each. The datasets included are Facebook Marketplace Data, Sales Prediction Data, and Wine Quality data.
correlation data-analysis data-science data-visualization knn linear-regression machine-learning matplotlib numpy pandas random-forest-classifier scikit-learn
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https://github.com/radinshahdaei/ce40215-nc
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jupyter-notebook numpy python sympy
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https://github.com/nathadriele/ifood-data-governance-pipeline
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airflow dashboard data-analysis data-catalog data-engineering data-governance data-quality data-visualization dbt ifood lgpd matplotlib numpy observability-data pandas pipeline pyspark redis seaborn streamlit
Last synced: 02 Apr 2026
https://github.com/broodhoney/blue-book-for-bulldozers
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matplotlib numpy pandas python scikit-learn
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https://github.com/lmizner/ece_c247_neuralnetworks
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https://github.com/pranavv34/customer-segmentation
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https://github.com/orliluq/inmersion-datos-python
Desarrollar modelos de machine learning para predecir la probabilidad de incumplimiento crediticio de los clientes, utilizando diferentes algoritmos de clasificación (Regresión Logística, Árboles de Decisión, Random Forest, Naive Bayes).
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https://github.com/harmanveer2546/nasa-asteroid-classification
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https://github.com/tharushi11/titanic-data-analysis
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https://github.com/christiemj/clock-drift-simulation
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https://github.com/kokila-m/data-quality-check-script-using-python
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https://github.com/tashi-2004/deep-learning-grid-world-q-learning
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https://github.com/prahaladhchandrahasan/object-localization
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https://github.com/quinnphil/math-for-programmers
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Last synced: 17 Apr 2026
https://github.com/kaushik-puttaswamy/exploratory-data-analysis-using-python
This project applies Exploratory Data Analysis (EDA) using visualizations like box plots, scatter plots, and correlation matrices. It helps identify patterns, select ideal functions via least squares error, and map test data while evaluating deviations.
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https://github.com/coder36459/fcc-projects
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Last synced: 03 Apr 2026
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A content-based movie recommendation system using deep learning to predict user ratings by leveraging user and movie features. The system integrates neural networks for feature extraction, utility scripts for data processing, and supports both new and existing user recommendations.
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https://github.com/anag0es/projetos-ml
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https://github.com/gregoritsch3/project_python_jobs_data_analysis
A multi-library Data Analysis Python project that draws useful insights from existing job data. It provides useful exploratory insight about job postings in the Data sector, such as the distribution of remote/non-remote jobs, jobs with/without healthcare, top paying and most demanded data roles, and more.
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https://github.com/mwoss/mownit
Various tasks from numerical analysis laboratories solved using Python
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https://github.com/prcharan592/social-media-sentiment-analysis
Social media sentiment analysis using tweets involves analyzing tweet data to determine public sentiment (positive, negative, or neutral) using natural language processing (NLP) and machine learning techniques.
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https://github.com/devllm/exemple-de-quantization
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https://github.com/nicovandenhooff/kaggle-competitions
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https://github.com/yassin522/music-genre-classification
This repository is dedicated to the Music Genre Classification project, an endeavor that leverages machine learning techniques to accurately classify music into various genres
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https://github.com/ahsouza/timenow
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Data analysis of retail meal orders, fulfillment centers, and product demand using Python
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https://github.com/gregoritsch3/ml_clustering_eda_customersegmentation
An EDA and Machine Learning Clustering exercise on the Mall Customer Segmentation synthetic dataset demonstrating the use of KMeans Clustering and the Elbow Method. The clustering algorithm successfully segments the customer base into groups distinguishable by their annual income and spending score.
clustering kmeans-clustering machine-learning matplotlib numpy pandas scikit-learn scipy seaborn
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https://github.com/jsnevt/regressao_linear
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Last synced: 18 Apr 2026
https://github.com/hariprasath-v/machinehack-analytics-olympiad-2022
Create a machine learning model to help an insurance company understand which claims are worth rejecting and the claims which should be accepted for reimbursement.
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