GitHub repository: sooryanivedhaashokan/Quick-Trip-planning-Assistant
Primary language: Python
Description:  Profitable Trip planning Assistant in US from JFK-New York Project Proposal:     In this project I would like to create a web application that suggest the best time to plan the trip based on the activity the user planning to do at any destination in US and would simulate various models for forecasting the future air fares and classifying whether to buy or wait for the reduction in air ticket fare based on historical trends. Aim of the project:   Input from the user:     US Destination: where to go     Travel start date : departure date       Trip activity - eg: skiing, trekking, relaxing, scuba diving etc   Output:     Weather condition of the destination     Suggest best time (month) of the year to visit the destination     List of destination you could also consider to travel on mentioned dates     Current air fares if you book immediately     Suggest the user to wait for to book ticket due to probability of  price down in the future To do list: Create a GUI using Tkinter Data collection:       Using scrapy web crawling framework to get data in csv database      Explore data collection automation techniques  Data Preprocessing:      Using pandas to do exploratory analysis of data Data Preparation:       Analyze data distribution      Extract required features - using Scikit-learn library Predictive model building using algorithms to forecast airfare drop       Explore ways to suggest the day to book the flight in cheaper rate