This book is a good practical introduction that walks you through the basic ideas as you develop some basic functionality. http://neuralnetworksanddeeplearning.com/
I'm often pretty skeptical of e-books and self publications, but the above link is pretty good (and the video series linked here references it as well.) The Goodfellow book that another commenter mentioned is a high-quality survey of the field and a nice, high-level overview of different research directions in deep learning, but isn't as pragmatic as an introduction.
If you're looking to understand the underlying theory behind deep learning, the Deep Learning book by Goodfellow et al. is awesome.
If you're interested in general machine learning, the Elements of Statistical Learning, by Tibsihirani et. al is great; a more applied book is Applied Statistical Learning by the same author.
For a more applied view, I'd check out Tensorflow or PyTorch tutorials; there's no good book, as far as I'm aware, because the tech changes so quickly.
I've done a series of videos on how to do deep learning that might be useful; if you're interested, there's a link in my profile.
