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: 2026-07-02 00:21:34 UTC
- JSON Representation
https://github.com/mdaltamashalam/uber-fare-prediction-models
Predicts the fare amount of Uber rides based on various factors such as pickup/drop-off coordinates, passenger count, and trip distance.
catboost data-analysis data-cleaning data-visualization lgbm-regressor machine-learning matplotlib numpy pandas python random-forest regression-models skit-learn xgboost-algorithm
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https://github.com/smahala02/materials-science-introduction
Introduction to Materials Science concepts using Python for array manipulation and visualization with NumPy and Matplotlib.
data-visualization materials-science matplotlib numpy python scientific-computing
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https://github.com/ryancswallace/npdb
Parallel NumPy-like interface for large n-dimensional arrays on disk.
mapreduce-designpatterns numpy numpy-arrays parallel-computing python
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https://github.com/alexixrugis/perceptronvisualization
Visualization of training and operation of a perceptron written from scratch in numpy
ai machine-learning numpy python
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https://github.com/sarowarahmed/predicting-kolkata-house-price
🏠 Predicting Kolkata House Price: A web app powered by a Machine Learning model, built with Numpy, Pandas, Scikit-learn, and Streamlit, to predict house prices in Kolkata. Deployed on Streamlit Cloud for easy access and real-time predictions.
app kolkata linear-regression machine-learning numpy pandas scikit-learn streamlit
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https://github.com/no0bitah/pdf-highlight-extractor
A Python tool for extracting highlighted text from PDF files while preserving formatting attributes (headers, bold, italic) and removing unwanted line breaks and page breaks. Perfect for integrating with content management systems.
automation crm documentation-tool numpy opencv pdf pdf-document-processor pillow pymupdf pypdfium2 python3 scrapping
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artificial-intelligence machine-learning numpy pandas python scikit-learn tensorflow
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https://github.com/murugavl/forage_tata_genai_powered_data_analytics
This repository showcases my work from the TATA GenAI Powered Data Analytics Virtual Experience on Forage, where I applied data cleaning, analysis, and visualization techniques to derive actionable business insights.
excel genai matplotlib numpy pandas powerbi python
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https://github.com/carterbox/libimage
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ai css data-science gradientboostinclassifier javascript logisticregression machine-learning matplotlib numpy pandas python randomforestclassifier seaborn streamlit supportvectormachine webdevelopment
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bar-charts box-and-whisker-plots correlation-analysis data-analytics data-visualization jupyter-notebook linear-regression numpy pandas-dataframe pandas-python r-value scatter-plot scipy scipy-stats
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https://github.com/yalai92/alfalfa_imp_exp_analysis
This repository covers data cleaning, analysis, and visualization of global alfalfa and pellet imports, focusing on trends from 2003 to 2023. It also includes a predictive analysis of global alfalfa demand for 2024-2029, using data science techniques to provide insights for stakeholders in the alfalfa industry.
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This project predicts car prices using machine learning models, including Simple and Multiple Linear Regression. It covers data acquisition, feature selection, and optimization techniques like Ridge Regression. The best model, Multiple Linear Regression, achieved an R² score of 0.84. Check out the full analysis in the repository!
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https://github.com/spoortimorabad/personally-identifiable-information-pii-
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A data analysis project aimed at analyzing the sales data of the super store and providing useful insight into customer preferences.
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This project is a Book Recommendation System that uses two main approaches: Popularity-Based and Collaborative Filtering. It recommends top books based on their rating frequency and average ratings, and also provides personalized book suggestions by analyzing user interactions.
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Scripts from a university data analysis project to approximate the decision tsp problem using heuristics and machine learning
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Investigate the film industry to gain sufficient understanding of what attributes to success and in turn utilize this analysis to create actionable recommendations for companies to enter the industry.
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Human Emotion Analysis using facial expressions in real-time from webcam feed. Based on the dataset from Kaggle's Facial Emotion Recognition Challenge.
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Developed a speech recognition system using TDNN, preprocessing audio, extracting MFCC features, and training the model. Fine-tuning with augmented data (19,000 rows) improved accuracy from 9% to 80% training and 40% validation. Data augmentation proved crucial for enhancing model performance and generalization. Still working to increase the acc.
deep-learning keras-tensorflow numpy os pandas tdnn tensorflow
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matplotlib numpy pandas python scikit-learn
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https://github.com/helosantosdesousa/analise-dados-titanic
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https://github.com/alejoduarte23/reading_data_from_dewesoft
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https://github.com/justin-marian/numpy-mlp
MLP from-scratch implementation only with NumPy, it supports regression and classification tasks.
classification lasso mlp numpy r2-score regression ridge
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https://github.com/type0-1/salary-truth-predictor
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linear-regression machine-learning matplotlib-pyplot ml numpy pandas polynomial-regression projects scikitlearn-machine-learning support-vector-regression
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imbalanced-learning numpy pandas python scikit-learn seaborn xgboost
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https://github.com/ahmedabdalkreem/hotel-reservation
Our task is to classify a Hotel Reservation as either booking canceled (class1) or no canceled(class0) and use more one model to arrive the best model.
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https://github.com/tansudasli/tensorflow-sandbox
all about machine learning
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https://github.com/5hraddha/sda-megaline-the-best-plan
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data-visualization hypothesis-testing matplotlib numpy pandas scipy seaborn statistical-data-analysis
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Clean Code Principles
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This model was built using Python and Logistics Regression algorithm
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