Yes well no net gets a 0 loss.
Mohan Karthik

Hi Mohan, thanks for the explanation. Suddenly i see your point of view! Trying to redo P3 right now though i have already cleared Term 1. Felt that there was still something i am missing out in P3 while i was building and training the model.

Just another question and feel free to explain only when you are free.

From your post i understand that you had used L/R images and flip images. That makes 6 images and choosing them randomly. Based on this method of feeding data to your model, wouldn’t it be more bias to feed L/R images (66%) than center image? If so, doesn’t it affect the training outcome.

I’ve tried your method of feeding through python generator and also feeding L/R images 25% of the time with center image 75% of the time where it seemed to drive better. Any opinions on that?

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.