To model this information, we utilized two approaches:
3-Layer Model: i did not expect the 3 layer model to do well. Whenever we develop any model, my objective is to get a model that is dumb first. This is my stupid model. We utilized a really architecture that is basic
The ensuing accuracy ended up being about 67%.
Transfer Learning making use of VGG19: The difficulty utilizing the 3-Layer model, is i am training the cNN on an excellent little dataset: 3000 pictures. The greatest cNN that is performing train on scores of pictures.
Being a total result, we utilized a method called « Transfer Learning. » Transfer learning, is simply going for a model some other person built and utilizing it on your own data that are own. Normally, this is what you want if you have a exceptionally little dataset.
Accuracy:73% precision
Precision 59percent
Recall: 44.61percent
Accuracy is simply predicting whether we disliked or liked the image properly.
Precision, informs us « out of the many profiles that my algorithm predicted were true, exactly how many did I actually like? » a low accuracy score will mean my algorithm would not be helpful since all the matches I have are profiles I do not like.
Recall, informs us « out of all of free doctor video chat room the profiles that we actually like, what amount of did the algorithm predict correctly? » If this rating is low, it indicates the algorithm is being extremely picky.
You can view here the algorithm predicting on Scarlet Johansson:
5. Operating the Bot
Now that i’ve the algorithm built, I needed seriously to connect it towards the bot. Builting the bot was not too hard. right Here, the bot can be seen by you doing his thing:
We deliberately included a 3 to 15 delay that is second each swipe so Tinder would not find out that it was a bot operating on my profile. Regrettably, I did not have enough time to add a GUI to the program.