Project Video Showcase
Airlines Delay Prediction Using Machine Learning and Deep Learning
Project Synopsis & Overview
This project aims to develop a predictive system for forecasting airline flight delays using machine learning and deep learning techniques. The system analyzes historical flight information and relevant factors such as departure and arrival times, flight distance, airline, airport traffic, weather conditions, mechanical issues, and crew-related factors. Data preprocessing, feature engineering, visualization, and exploratory data analysis are performed before model training. Machine learning models such as Decision Tree, Naive Bayes, Random Forest, Logistic Regression, KNN, and SGD, along with deep learning models such as Neural Networks, LSTM, RNN, and CNN, can be used for prediction. The models are evaluated using accuracy, precision, recall, F1-score, and confusion matrix, and their performances are compared.
Complete Technical Specifications
| Project ID | 1CP0631 (DB ID: 631) |
| Project Title | Airlines Delay Prediction Using Machine Learning and Deep Learning |
| Domain Division | Python |
| Sub-Domain / Tech | AI |
| IEEE Year | 2026 |
| Package Price | ₹6500 |
| Created Date | Sep 17, 2026 |
Call or WhatsApp our technical lead directly at +91 79043 20834