B
Brokeland
its a real estate app for selling plot of both commercial and agricultural land using ML such as calculating yeild point and comparing agricultural plot on yeild productivity basis
B
Brokeland
its a real estate app for selling plot of both commercial and agricultural land using ML such as calculating yeild point and comparing agricultural plot on yeild productivity basis
The problem Brokeland solves
Reduces the cost of commission taken by middle man and brings transparency in the buying and selling process
Challenges we ran into
The hurdle we encountered was using ML and Flask together. The biggest hurdle that we encountered was chosing between the 2 types of Flask web frameworks:Flask and Flask-RESTful as we had no clue what was used for what purpose. After watching a couple of youtube videos we finally decided to use Flask-RESTful as it was much clearer and made the code much more lucid. The only hurdle that we were not able to overcome was using the POST request remotely through the URL obtained via ngrok. However the curl post request worked successfully in the localhost.
Technologies used
Discussion