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/jcm-ai/robust-mlops-elevating-machine-learning-to-production-scale
This project aims to address the challenge faced by the Office of Foreign Labor Certification in managing a high volume of job certification applications for employers seeking to hire foreign workers in the United States. By leveraging ML models, this project seeks to streamline the process of shortlisting visa applicants based on historical data.
aws-ec2 aws-ecr aws-s3 cicd-pipeline data-science docker-image end-to-end exploratory-data-analysis git github-actions html machine-learning-models mlops mlops-project model-deployment mongodb numpy pandas python yaml
Last synced: 09 Apr 2026
https://github.com/geetu040/fetcher
AI GAME: We have a random maze and 2 agents at random places. You control the Fetcher and find the way through the maze to get ot the target. You can automate the Fetcher to use trained models that help Fetcher fetch the target by itself. The models are based on deep neural networks, implemented by tensorflow and Keras API. The models are so efficiently trained, they find ways through the maze without hitting the walls and have an accuracy of more than 99%
artificial-intelligence css deep-learning html javascript jupyter-notebook machine-learning matplotlib neural-networks numpy python sklearn tensorflow web-design
Last synced: 13 Apr 2026
https://github.com/dmarks84/coursework_project_network-analysis-node-link-prediction
Project for University of Michigan Applied Data Science Specialization -- Analyzed network nodes and edges, developing custom features based on various scoring metrics; used features to train classifier model to predict node attribute (employee salary type) and future edges (employee connections)
classification cross-validation data-reporting databases eda grid-search matplotlib network-analysis numpy pandas python scikit-learn statistics supervised-ml visualization
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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.
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https://github.com/pythonhealthdatascience/stars-reproduce-lim-2020
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https://github.com/vedikasnehil/daily-leetcode-
Daily LeetCode Using Python is a project dedicated to solving coding challenges consistently using Python. It focuses on improving problem-solving skills, mastering Python techniques, and building a collection of clean, well-documented solutions. Perfect for interview preparation, learning algorithms, or daily coding practice!
matplotlib numpy pandas python python3 seaborn
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Create comprehensive customer profiles for each AeroFit treadmill product through descriptive analytics. Develop two-way contingency tables and analyze conditional and marginal probabilities to discern customer characteristics, facilitating improved product recommendations and informed business decisions.
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As a newly hired AI Engineer, your task is to predict customer behavior based on various features such as age, income, and gender. This exercise involves cleaning the data, training a decision tree model, and evaluating the model's performance to understand the key factors influencing customer purchasing decisions.
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Linear Regression experiments on the California Housing dataset across five phases, using NumPy and scikit-learn only (no pandas). Includes EDA, polynomial features, SGD with scaling, residuals, 5-fold CV, and an LNCS-style report with figures.
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https://github.com/fairlytales/machine_learning
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https://github.com/jatin-mehra119/paris_housing_price-kaggle-
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https://github.com/aaaastark/breast_cancer_analysis
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data-science dataset machine-learning numpy pandas python sklearn tensorflow
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https://github.com/sayidmushtaq/reportcard
Tracking and analyzing student grades. It calculates averages, identifies top performers, and generates performance reports with ease.👨🏼🎓👨🏼🎓
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https://github.com/jsimell/sleepanalysis
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data-analysis matplotlib numpy pandas python scikit-learn seaborn
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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
Last synced: 17 May 2026
https://github.com/hansalemaos/cirdhighspeedcoverter
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https://github.com/ljubogdan/solar-cycle-lstm
This project predicts sunspot activity using an LSTM model for time series data. Built with TensorFlow and Keras, it uses Huber loss for outlier handling and MAE for performance evaluation. The dataset, sourced from Kaggle or SIDC, spans over 270 years of monthly sunspot data.
conv1d huber-loss-regression kaggle keras lstm machine matplotlib numpy pandas scikit-learn seaborn solar sunspots tensorflow time-ser
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https://github.com/anish37860/python_party
Python summer party by Interview Master & in partnership with DataCamp
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data-analytics numpy pandas python3
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https://github.com/farhad-here/predict_student_performance
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https://github.com/juzershakir/train_a_smartcab_to_drive
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photo and album organizer for gtk3
gtk3 numpy opencv-python photography pil pillow python
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https://github.com/harmanveer-2546/reducing-data-entries
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csv data data-entry delete-data excel numpy pandas python
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math matplotlib numpy probality-theory scipy-stats statistics
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https://github.com/shreshthvashisht/bank-loan-case-study
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Chi2 contengency independence test Q4. TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5
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Data Analysis according to sale data.
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Transform smartphone photos into scanned documents in seconds! This Python-based document scanner automatically detects edges, corrects perspective, and enhances document images to produce clean, scanner-like results.
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Predicting Titanic passenger survival through machine learning. This project includes data preprocessing, exploratory data analysis, feature engineering, and model training using Python. 🚢
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📈 Advertising Sales Predictor: A web app powered by a Machine Learning model, built with Numpy, Pandas, Scikit-learn, and Streamlit, to forecast sales based on TV, Newspaper, and Online Advertising. Deployed on Streamlit Cloud for real-time, easy-to-use predictions.
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https://github.com/sharkb8t/credit-risk-classification
Demonstrates my abilities to use Jupyter Notebook with scikit-learn to train and evaluate a machine learning model.
jupyter-notebook numpy pandas pathlib python scikit-learn
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https://github.com/linggarm/evolutionary-algorithms
Collection of codes of Evolutionary Algorithms college course (Knapsack Problem & Travelling Salesman Problem)
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Complete statistical analysis of cavy lifetime dataset using Python, Pandas, NumPy, Matplotlib, and SciPy to explore, visualize, and infer the impact of bacilli infection on cavy lifetimes 🦫
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https://github.com/rampal-punia/data-science-toolkit
Your Go-To Resource for Essential Data Science Related Commands, Concepts, Quick Overviews and Useful Functions.
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