Flight Fare Prediction Machine Learning Project with Deployment | Time Series | Project#10

🔥 Flight fare prediction is a classical problem of time series forecasting that find trends in past observations to outline the future. GitHub Project Repo: https://github.com/skillcate/flight-price-prediction Google Drive Project Folder: https://drive.google.com/drive/folders/1vnapi048bbmoXyoxOLLX6W_tA6a1uQ9w?usp=sharing Skillcate Discord Server: https://discord.gg/r42Kbuk Many popular flight booking websites today, including Google Flights, showcase important insights on: current fair status: high, low or fair; past / upcoming fare trends; and essentially, helps decide the right time to book a flight ticket. In this project, we are going to build a Python Flight Fare Prediction App, that returns the fare prediction for a given set of travel details, like: departure date, arrival date, departure city, arrival city, stoppages, and the airline carrier. 🔥 Sections: 00:00 Introduction 01:49 Our Plan of Action 05:18 EDA (Feature Engineering) 14:20 Feature Selection 17:41 Model Training 19:30 Predictions on Fresh Data 22:24 Flask Deployment 31:17 Let's talk Machine Learning 🔥 During the course of next ~30mins, we shall discuss: a. Business use-case for Flight Predictions b. Feature Engineering on Object Variables (using: pandas to.datetime function) c. Feature Engineering on Categorical Variables (using: OneHotEncoding & LabelEncoding) d. Feature Selection using Sklearn Feature Importance & Variable Inflation Factor (VIF) - for Multicollinearity check e. Training Fare Prediction - Random Forest Regressor Model f. GitHub Project Repo Walkthrough (including web app.py) g. Flask Deployment of Project App 🔥 Important Links: Dataset Source: https://www.kaggle.com/datasets/nikhilmittal/flight-fare-prediction-mh Sentiment Analysis Project based Review Classification Project from Skillcate: https://youtu.be/zwR6M5zpnWs Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask): - Model Building: https://youtu.be/lKAdxN0qrgk (Part-1) - Model Deployment: https://youtu.be/KEQCVwJU5KU (Part-2) 🔥 Do like, share & subscribe to our channel. Keep in touch: Skillcate Discord Server: https://discord.gg/r42Kbuk Email: [email protected] Website: https://www.skillcate.com Facebook: https://www.facebook.com/groups/mlprojects Telegram: https://t.me/skillcate