@dujegilja wrote:
Hi all,
I created web scraper that would collect car data from a particular site. I collected little more than 1000 cars (different Audi models) and some information about them.
I wanted to use the dataset to predict the prices of cars. I know that there are different models that can be used, but for the beginning I wanted to do simple linear regression as that is a good way to actually learn and understand what one is doing - plugging everything in some NN or random forest might yield good results but I would get no understanding out of it as it would just be a black box which spits out the solution.
So, suggestions about different methods are welcome, but I would really like to solve this the simplest way possible or understand why it is not possible to do it that way.I am providing dataset and complete code with all the explanations and procedure of what is being done and why.
This might also be a great material for other people just beginning as everything is explained in detail.The problem is that predictions I get are really off and I am having a hard time understanding what I am doing wrong or if I am missing something. I am really looking forward to everyone’s feedback.
One of the following links should work. There you can see code with explanations and also dataset used.
Or
OR
Posts: 1
Participants: 1