I'm starting to learn Machine learning from Tensorflow website. I have developed a very very rudimentary understanding of the flow a deep learning program follows (this method makes me learn fast instead of reading books and big articles). 

There are a few confusing things that I have come across, 2 of them are:

1. Bias
2. Weight

In the MNIST tutorial on tensorflow website, they have mentioned that we need bias and weight to find the evidence of the existence of a particular pattern in an image. What I don't understand is, where and how the values for Bias and Weight are determined? 

Do we have to provide these values or does the TensorFlow library calculates these values automatically based on the training data set?

Also if you could provide some suggestions on how to accelerate my pace in deep learning, that would be great!

[Tensorflow Beginners Tutorial](https://www.tensorflow.org/get_started/mnist/beginners)