Research into Deep Learning has come a long way across multiple domains, such as healthcare, marketing, banking, manufacturing, education, and so on. Notable applications within these domains are trending, like visual recognition, fraud detection, virtual assistance, NLP, etc. Deep Learning models are used to implement these applications. Those models include Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and others. To deploy these application-based Deep Learning models, Python programing is ideal, with its open source software libraries like Keras, Tensorflow, and soon. This book thoroughly explains Deep Learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). This book provides hands-on guidance to using Python for implementing Deep Learning application models. It also identifies future research directions for Deep Learning.