We covered a lot of ground in this chapter as regards the fundamentals of deep learning. We really commend your efforts on getting this far! The idea of this chapter was to introduce you to the core concepts and terminology pertaining to the domain of deep learning. We started with a brief introduction of deep learning and then looked at the popular frameworks in today's deep learning landscape. Detailed step-by-step guides have also been included for setting up your own deep learning environments to develop and train large-scale deep learning models on GPUs.
Finally, we covered essential concepts around neural networks including linear and non-linear neurons, data representation, chain rule, loss functions, multilayer networks, and SGD. The challenges of learning in neural networks were also covered, including popular caveats surrounding local minima and exploding...
