Deep Learning with Applications Using Python

Book Description Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning.

This book covers convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. 

What You Will Learn 

• Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn.
• Use face recognition and face detection capabilities
• Create speech-to-text and text-to-speech functionality
• Engage with chatbots using deep learning

Who This Book Is For
Data scientists and developers who want to adapt and build deep learning applications.

Content

Chapter 1: Basics of TensorFlow
Chapter 2: Understanding and Working with Keras
Chapter 3: Multilayer Perceptron
Chapter 4: Regression to MLP in TensorFlow
Chapter 5: Regression to MLP in Keras
Chapter 6: Convolutional Neural Networks
Chapter 7: CNN in TensorFlow
Chapter 8: CNN in Keras
Chapter 9: RNN and LSTM
Chapter 10: Speech to Text and Vice Versa
Chapter 11: Developing Chatbots
Chapter 12: Face Detection and Recognition