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/pramodyasahan/spaceship-titanic
This repository features a machine learning model designed to predict whether passengers of a space travel company are likely to be transported. The model employs CatBoostClassifier, a machine learning algorithm known for handling categorical data effectively.
machine-learning numpy pandas python scikit-learn
Last synced: 13 Apr 2026
https://github.com/bropenguin847/python-learning
Learning Python for Scientific Programming. Intended for beginners with some knowledge of Python.
array-manipulations convolution jupyter matlab matplotlib-pyplot numpy pandas-python pep8 python python3 scientific-programming scipy spyder-ide vscode
Last synced: 13 Apr 2026
https://github.com/rajan-bhateja/data-analysis-with-python
Cleaning, analysis and visualization on various datasets using Python and its various libraries via Jupyter Notebook
data-cleaning data-science jupyter-notebook matplotlib numpy pandas python seaborn
Last synced: 30 Apr 2026
https://github.com/ot-code/coca-cola-stock-prediction
This repo compares four predictive models—Linear Regression, ARIMA, XGBoost, and LSTM—to forecast Coca‑Cola FEMSA stock closing prices using Python and five years of historical data.
arima csv linear-regression lstm-neural-networks mae matplotlib mse numpy pandas python r2 scikit-learn seaborn tensorflow-keras xgboost
Last synced: 13 Apr 2026
https://github.com/csengupta1101/netflix-rating
The project revolves around Netflix shows and movies around the world. The problem statement that is being tried to address here is that what kind of show to come up with in future times and how well that will fit with the audience
jupyter-notebook matplotlib movies netflix numpy pandas plotly python python3 rating tvseries
Last synced: 13 Apr 2026
https://github.com/paulo-freitas-junior/ifood-dev-week2023
Repositório sobre a Dev Week iFood sobre uso de Python e Inteligência Artificial para realização de cálculo de NPS ( Net Promoter Score ) e a utilização de IA para análise de sentimentos dos comentários usando tecnologia do ChatGPT-4.
bert chatgpt colab-notebook matplotlib nltk numpy pandas python textblob-sentiment-analysis
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https://github.com/nicolascoiado/nivel-mar
Este projeto realiza uma análise detalhada do nível médio global do mar (GMSL), utilizando uma base de dados pública que abrange medições históricas. O objetivo é explorar tendências, calcular a taxa média de elevação e visualizar os dados por meio de gráficos.
google-colab jupyter-notebook matplotlib numpy pandas python python3 scikit-learn
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https://github.com/muskan-setiya/spotify-data-analysis
Used Spotify.csv from Kaggle
matplotlib numpy pandas python seaborn tableau
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https://github.com/fabriziomusacchio/ann_with_numpy
A how-to for building an artificial neural network from scratch using NumPy
ann artificial-neural-networks neural-network numpy
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https://github.com/shreeparab1890/heart-attack-analysis-prediction-accuracy-85.24
This iPython Notebook implements the Analysis and Predictions for Heart Attack. The Analysis is done on the dataset to identify the key features which has a impact on Heart Attack. After the analysis and data cleaning, the dataset is used to train the model using different ML algorithm.
eda exploratory-data-analysis matplotlib numpy pandas plotly prediction python scikit sklearn
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https://github.com/hilalozdemirbuyukasik/deep-learning
A collection of deep learning projects demonstrating RNNs, BiLSTMs, CNNs, and basic neural networks applied to time series forecasting, text sentiment analysis, image classification, and tabular data tasks, with examples of data preprocessing, model training, evaluation, and visualization.
bilstm cnn keras matplotlib nn numpy rnn scikit-learn tensorflow
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https://github.com/waghraj1699/codeclauseinternship_crop_disease_identification
Crop Disease detection app,it predicts wheather the given image of crop has disease or not.
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https://github.com/takana671/partiallytransparentimage
A simple tool to make an image partially transparent
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https://github.com/aiwithqasim/ab-testing-for-shoefly.com
In this project, I had analyzed the data set of SHOEFLY.COM to find out valuable insights to check which platform is more useful for advertisement.
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https://github.com/spear97/montecarlo-simulaton
This project involved developing a Monte Carlo Simulation using Python, implemented with libraries like NumPy, Pandas, and Matplotlib within Visual Studio. The program's primary goal is to generate figures illustrating compound interest results over time for a specified amount.
data-science matplotlib matplotlib-figures numpy pandas-python python python-3 python3
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https://github.com/patex1987/ghcn-temperature-dataset
Analysis of GHCN (Global Historical Climatology Network) temperature dataset using Numpy
climate-data jupyter-notebook numpy python temperature-data
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https://github.com/yash-3-bit/pubg-game-prediction
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https://github.com/18mahi/digital_cave
An intermediate-level deep learning project that compares Convolutional Neural Networks (CNN) and Multi-Layer Perceptrons (MLP) on the MNIST handwritten digits dataset. This project demonstrates data augmentation, learning rate scheduling, and visual comparison of model performance
cnn confusion-matrix data-augmentation data-science deep-learning evaluation-metrics jupyter-notebook keras learning-rate-scheduler machine-learning matplotlib mlp numpy python3 scikit-learn seaborn tensorflow
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https://github.com/pranavsp108/time-series-forcasting
A time-series forecasting project to predict hourly energy consumption using Python, Pandas, and an XGBoost regression model.
data-analysis data-science energy-consumption forecasting matplotlib numpy pandas python scikit-learn sustainability time-series xgboost
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https://github.com/ahmadbuilds/fake-news-classifier
Classifies news articles as real or fake using an NLP pipeline with TF-IDF + n-grams and machine learning models. Includes text preprocessing, feature engineering, model training, and evaluation.
fastapi logistic-regression matplotlib n-grams nextjs nltk numpy pandas python3 random-forest-classifier react scikit-learn seaborn supervised-learning tf-idf typescript xgboost-classifier
Last synced: 11 Apr 2026
https://github.com/elvisrock/government_analysis
Esse projeto, tem como objetivo, analisar, explorar algumas técnicas e propor uma sugestão ao governo de forma geral, sem qualquer viés politico.
data-science machine-learning numpy pandas python sklearn
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https://github.com/dibsthegreat/titantic-dataset-analytics
DASC4850 Final Project where I did EDA to determine the survivability of Titanic guests depending on Age, Gender, Wealth, etc.
data-science data-visualization matplotlib numpy pandas python random-forest-classifier
Last synced: 13 Apr 2026
https://github.com/sudharshan-bathini/chat-bot-using-cornell-movie-data-set
Developed an AI chatbot using the Cornell Movie Dialogs dataset; trained an LSTM-based model to generate context-aware, conversational responses for user inputs.
keras lstm-sentiment-analysis neural-networks nlp numpy python tensorflow tokenizer
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https://github.com/thejvdev/ml-from-scratch
Repository for Implementing ML Models from Scratch in Python
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https://github.com/zolppy/recommendation-system
This project demonstrates the creation of a content-based image recommendation system. It leverages a pre-trained VGG16 deep learning model to extract meaningful feature vectors from images. These features are then compared using cosine similarity to identify and recommend visually similar images.
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dashboard exploratory-data-analysis matplotlib-pyplot numpy pandas powerbi seaborn
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https://github.com/hmotez/medclaimml
An AI-powered machine learning application designed to process healthcare reimbursement claims. It analyzes medical documents, client information, insurance policies, and legal regulations to predict accurate reimbursement amounts, ensuring efficiency, compliance, and fraud detection.
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https://github.com/ellennewerkla/eda_students_performance
EDA em Python com Pandas, Matplotlib e Seaborn para identificar padrões de desempenho em estudantes.
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ChatGPT said: This project analyzes and predicts the health of coral reefs in the Florida Keys by examining coral cover and species richness trends over time.
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Project for University of Michigan Python Programming Specialization -- Read in documents with images and text, and utilized CV libraries/packages to extract specific types of images and text, pairing them together
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https://github.com/sohitbennett/roadsafe
A Deep learning computer vision system for real-time traffic safety monitoring.
computer-vision esrgan keras numpy pandas python scikit-learn tensorflow tesseract-ocr yolov5 yolov8
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https://github.com/gurramankit/censusproject_ml_randomforest
The objective of this project is to build a classification model using the Census Income dataset from the UCI Machine Learning Repository. The model predicts whether an individual's income exceeds $50,000 per year, based on their demographic and employment-related attributes.
matplotlib numpy pandas python random-forest scikit-learn seaborn
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https://github.com/farhannirzhor/python_eda_project_on_diwali_sales_analysis
In this project, I was given a sales data. I analyzed their sales data and shared a summary
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https://github.com/tnel7/data-science-yandex-practicum
Проекты из Яндекс Практикума "Специалист по Data Science"
data-science machine-learning nlp-machine-learning numpy pandas seaborn sklearn
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https://github.com/dpbm/extract_frames
extract frames from videos
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https://github.com/salma-mamdoh/the-android-app-market-on-google-play-project
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https://github.com/fairlytales/machine_learning
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jupyter-notebook machine-learning machine-learning-algorithms matplotlib numpy opencv opencv-python pandas python pytorch scikit-learn scipy
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https://github.com/omcodewizard/nasa-battery-analysis
This repository contains code for analyzing battery data from NASA's battery testing dataset. The analysis involves processing battery impedance, electrolyte resistance, and charge transfer resistance across charge/discharge cycles to track the aging and performance of various batteries.
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https://github.com/sultanazhari/game-trend
Ice as a online store Video Games want to know a new trend of video game to help them prepare a video games which is more profitable to sell. As a data Analyst we're giving a trend of video game by genre, platform, console and the others clasification.
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This is Python based project which is a virtual board and we write there using our finger and clear it and color changing.
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https://github.com/dwija12903/ai-lab
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keras numpy sckit-learn tensorflow
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This project involves conducting A/B testing to evaluate the performance of two marketing campaigns: Facebook Ads and Google Adwords for an online retail business. The primary goal is to determine which campaign is more effective in driving user engagement and conversions, helping the company optimize its marketing strategies.
ab-testing linear-regression matplotlib numpy pandas python scipy seaborn sklearn-
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haskell hmatrix numpy optimization python qr-algorithm symmetric-matrix
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data-science dataset machine-learning numpy pandas python sklearn tensorflow
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https://gitlab.com/DLR-SY/boxbeam
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Notas de la materia "Inteligencia Artificial" para su posterior extraccion mediante algun modelo de lenguaje que nos permita dar respuestas personalizadas con base a la informacion presente en este repositorio.
ai matplotlib numpy pandas phaserjs python scikit-learn
Last synced: 21 Jan 2026
https://github.com/chandkund/sms-spam-detection
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matplotlib nlp-machine-learning numpy pandas seaborn stemming tfidf-vectorizer tokenization
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https://github.com/achronus/data-graphing-tool
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data-visualization matplotlib numpy pandas python3
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https://github.com/abideen-olawuwo/heart-diseases
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decision-tree-classifier kneighborsclassifier logistic-regression matplotlib numpy pandas python random-forest-classifier scikit-learn seaborn
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https://github.com/shubham-bendre/football-clip-analysis
This project uses YOLO and Roboflow datasets to analyze football matches, detecting players, referees, and the ball while tracking movements in real-time.
deep-learning matplotlib numpy roboflow-dataset yolov5
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https://github.com/hoyirul/flask-starter-fs
Flask-Starter-FS is a concise full-stack starter kit for Flask web development, offering quick setup and pre-configured settings for seamless integration of front-end and back-end components. Accelerate your full-stack web application development with Flask-Starter-FS.
flask machine-learning numpy pandas python sklearn
Last synced: 14 Apr 2026
https://github.com/chewzzz1014/data-analysts-projects
coursework jupyter-notebook matplotlib numpy pandas python seaborn
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https://github.com/5hraddha/ice-video-games-sales-analysis
Analysis of video game sales data of an online store Ice, which sells video games all over the world & identify patterns that determine whether a game succeeds or not.
data-visualization matplotlib numpy pandas requests-module scipy seaborn
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https://github.com/hossein-cod/parking-space-detection
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cv2 jupyter-notebook numpy opencv pickle python
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The "Gold Price Prediction" project focuses on predicting the prices of gold using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, Random Forest Regressor, and others, this project provides a comprehensive solution for accurate price estimation.
data-science google-colab-notebook jupyter-notebook machine-learning matplotlib numpy pandas-dataframe python seaborn sklearn
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https://github.com/mbarbetti/hello-snakemake
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https://github.com/sunilvarma-l/liverdiseaseprediction
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https://github.com/samir-atra/experiments_and-_improvements
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Predicting the Sale Price of Bulldozers Using Machine Learning 🚜💰 This project uses machine learning to predict bulldozer sale prices based on historical data from the Kaggle Bluebook for Bulldozers competition. The goal is to minimize the RMSLE between actual and predicted prices.
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https://github.com/sonaligill/olympics-analysis
The outcome of this project is an interactive streamlit web application that visualizes the analysis of Olympic data while rendering different aspects of Olympic history, compare country performances, and gain insights into athlete demographics.
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https://github.com/harmanveer2546/heart
Predicting the presence of heart disease based on several health-related factors and Performing - i.) Data Cleaning ii.) Data Pre-Processing iii.) EDA iv.) Compare 5 different classification algorithms (Logistic Regression, Decision Tree, Random Forest, KNN and SVC)
data-preprocessing decision-tree eda knn logistic-regression machine-learning numpy pandas random-forest roc-auc-curve svc
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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.
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https://github.com/alejandro945/insurance-risk
This project aims to predict the risk of insurance claims using a dataset from Kaggle. The dataset consists of 26 columns and 205 rows, providing various features related to insurance risk. By analyzing this data, we seek to build predictive models that can help insurers assess the risk of claims.
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https://github.com/slovnicki/matematicki-softver
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https://github.com/ambrish8/bell-s-palsy
BELL’S PALSY SEVERITY DETECTION USING DEEP LEARNING
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https://github.com/drsartoriuss/portfolio
Учебные проекты из Яндекс Практикума "Специалист по Data Science+"
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In this project, we try to predict the possibility of canceling the plane ticket by the buyer
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https://github.com/asherk7/house-price-prediction
House Prices - Advanced Regression Techniques - Predict sales prices and practice feature engineering, RFs, and gradient boosting
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Last synced: 15 Apr 2026