Projects Using scikit-learn
17 projects
Learn more about scikit-learn → Combine with other filters →Satellite Image Classification
Teach a computer to read the Earth from space
Train a machine learning model to classify satellite images by land type — urban, forest, water, agriculture. A perfect first ML project using real remote sensing data.
Start Project → Some AI/MLRemaining Useful Life Prediction with scikit-learn
Predict when a turbofan engine will fail before it does.
Build an end-to-end machine learning pipeline on the NASA C-MAPSS dataset to estimate turbofan engine remaining useful life (RUL). You will engineer features from raw sensor streams, train regression models, and evaluate prognostic accuracy using RMSE and scoring functions from the prognostics literature.
Start Project → Some AI/MLSatellite Telemetry Anomaly Detection
Catch satellite failures before they happen using unsupervised ML
Apply unsupervised clustering algorithms to real satellite telemetry datasets to detect anomalous behavior patterns before they escalate into failures. Combines signal processing, feature engineering, and scikit-learn to build a production-ready anomaly detection pipeline.
Start Project → Some AI/MLTest and Compare Material Strength with a Simple ML Model
Break things on purpose, then teach a computer to predict the results
Build and break popsicle-stick or balsa-wood structures, record their dimensions and failure forces, then train a scikit-learn linear regression model to predict strength from geometry. A hands-on bridge between physical testing and machine learning.
Start Project → Some AI/MLPredict Composite Laminate Failure with scikit-learn
Teach a model to predict how and where a composite will fail
Generate a dataset of composite laminate configurations using classical laminate theory, then train a multi-class classifier to predict failure mode — delamination, fiber breakage, or matrix cracking — from layup parameters. Bridges textbook composites theory with practical ML.
Start Project → Some AI/MLPredict Model Rocket Altitude from Motor Data with Python
Use real thrust curves and simple physics to predict how high your rocket will fly
Build a dataset from published model rocket motor thrust curves and basic physics, then train a scikit-learn regression model to predict peak altitude from motor impulse, rocket mass, and drag estimate. Combines rocketry fundamentals with your first predictive ML model.
Start Project → Some AI/MLPredict Jet Engine Thrust from Sensor Data with Random Forest
Use NASA engine data to learn what sensor readings reveal about thrust
Use the NASA C-MAPSS turbofan engine simulation dataset to build a regression model that predicts thrust output from temperature, pressure, and spool speed sensor readings. Explore feature importance and gain insight into gas turbine thermodynamics through data.
Start Project → AI/MLMeasure and Classify Sounds Around an Airport with Python
Record real-world sounds and teach a computer to tell them apart
Record or download airport-area sounds — jet engines, propeller aircraft, ground vehicles, birdsong — and train a scikit-learn classifier to distinguish sound types using simple audio features extracted with librosa. A hands-on introduction to audio machine learning.
Start Project → AI/MLPredict Tomorrow's Wind Speed for Flight Planning
Build a weather model that helps pilots make go/no-go decisions
Download historical airport weather data (METAR observations) and build a simple machine learning model that predicts next-day wind speed. Learn how pilots use weather forecasts for flight planning and go/no-go decisions.
Start Project → AI/MLPredict Clear-Air Turbulence from Weather Data
Build a classifier that warns pilots about invisible rough air
Build a machine learning classifier that predicts turbulence severity (none/light/moderate/severe) from atmospheric variables using real NOAA pilot reports (PIREPs) and reanalysis data. Tackle one of aviation's most challenging weather hazards.
Start Project → Some AI/MLClassify Aircraft Types from ADS-B Trajectories
Identify what's flying overhead from how it flies
Extract flight trajectory features from OpenSky Network ADS-B data — climb rate, speed profile, turn radius, acceleration patterns — and train a classifier to identify aircraft types. Learn feature engineering on spatiotemporal data.
Start Project → Some AI/MLPredict Flight Fuel Burn from Route and Aircraft Data
Build an ML model that estimates fuel consumption before takeoff
Use publicly available flight data from BTS or Eurocontrol to build a regression model predicting fuel consumption from distance, aircraft type, payload, and weather. A real-world ML problem with direct sustainability applications.
Start Project → Some AI/MLBuild a Word Cloud and Classifier from Aviation Safety Reports
Mine real incident reports to discover what goes wrong in the cockpit
Download NASA ASRS incident summaries, create word clouds for different incident categories, then train a simple text classifier to categorize new reports. A hands-on introduction to natural language processing with real safety data.
Start Project → AI/MLAnalyze Aviation Incident Patterns with NLP
Apply modern NLP to uncover hidden patterns in safety data
Use the NASA ASRS database to classify incident narratives by category using TF-IDF and transformer models. Discover patterns in human-factors incidents that traditional analysis methods miss.
Start Project → Some AI/MLBuild a Flutter Demo and Predict Vibration Frequency
Feel aeroelasticity with a homemade wing in front of a fan
Build a simple cantilever wing from cardboard or balsa, measure vibration frequency at different wind speeds using a phone accelerometer, then fit a regression model to predict frequency from speed.
Start Project → Some AI/MLMeasure Heat Dissipation and Predict Cooling with Python
Newton's law of cooling meets machine learning in your kitchen
Heat small metal and plastic samples, log temperature over time, fit exponential cooling curves, and predict how long different materials take to cool. A hands-on experiment connecting thermal physics to data science.
Start Project → Some AI/MLPredict Avionics Bay Temperature with Regression Models
Build an ML model for the thermal challenge every aircraft faces
Build a regression model predicting peak avionics bay temperature from flight phase, ambient conditions, and power dissipation. Use synthetic data from thermal network models to train and validate your approach.
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