The contents here are quite good with examples for each section, there is probably an Udemy course related to this (if you are willing to pay).
Or pick on the topic from the content and use blogs, youtube tutorials and github codes to educate yourself on the specific technique (CNN or RNN) you need to work on.
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.
Deep learning is a sub-field of machine learning, which is, in turn, a sub-field of artificial intelligence (AI). For you to understand and evolve, I suggest you start from basic machine learning especially simple linear regression, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM) and the likes, then to Artificial Neural Network (ANN) and finally to CNN.
The reason being that all machine / deep learning interfaces are the same.
Example:
vGG = VGG16(); vGG.predict(x);
resnet = ResNet(); resnet.predict(x);
I know it may take time but will come with quality understanding. You can follow up on the resource provided by @ Rayson Laroca too but for experts. You may have all the resources but if you don't build a basic understanding, you may end up applying peoples model. if you're not in a hurry, then i suggest @ Tahmina Zebin link. It takes you through from A-Z but you have to pay.
Someone once shared with me this link of Dr. Adrian Rosebrock's source codes and a review of his book ' Deep Learning for Computer Vision with Python' , which I would suggest you get the Starter Bundle. But before you do, read everything in the link shared with me below.
Pankas, there are too much complicated information out there about Deep Learning, and most the time they will not start from the beginning, making it even more complicated. I am suggesting you this Deep Learning simplified video from YouTube to start with. It will help you understand the concept.