I am a computer science student with about one semester left before graduation. Currently, I have some free time — about a month before the final semester begins.
I am interested in artificial intelligence (AI) and have taken classes / projects in machine learning. I am currently using this time to read / revise machine learning theory from Christopher M. Bishop's Pattern Recognition and Machine Learning [PDF, 18 MB]. I am doing this purely because I am interested in the mathematics and statistics behind machine learning.
I feel like going so in-depth into machine learning theory is only good for academia (research). I do not see how such theory will be applied in the future should I take a job on developing AI systems which is more end to end machine learning.