Hey. Thanks for reading my post!
I am trying to make a machine learning model that is capable of building the most efficient system given some data. An example: You want to build a specific thing such as a treehouse. You can choose different material which each can all have different advantages. Given the price, how long it lasts, average length, weight it can hold, etc. how can you choose what materials you will use to get the best outcome given a budget and size of the treehouse?
I’ve completed the Python3 course and I’m in the middle of machine learning. I still haven’t gotten any ideas for what I could do for this case. Any help is appreciated.
Thanks!
The idea is good. I believe what you are trying to do is similar to recommendation system. There are several way you can build a recommendation system model in ML. You can use Python. Or you can use TensorFlow as well. Try to build your idea from the ground. Then start collecting data.
I did a bit of research about recommendation systems and I found 2 main types, Collaborative filtering and Content based filtering. Collaborative filtering is more like recommending something that is the most popular which is not what I’m shooting for. Content based filtering is more like recommending things that are similar to what a user likes. I’m also not shooting for this. Do you know a specific type of recommendation system that would be more optimal for this? Given that you have data that is needed, what recommendation system would be the most accurate at recommending the best materials that I would use(not the most popular overall or not the most related to the user)?
Thanks!