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.
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.
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