Future of Sports in AR/VR

AR And VR in Professional Sports “The Two” are already here and are making a good impact over the entire industry. It’s naturally coming into the daily lives of every person associated with sports including the audience, players, and investors.   Researchers are working to increase its potential and usability Read more…

Types of VR Devices

The majority of Virtual Entertainment (VE) systems that are currently available to purchase require a personal computer to power them. And these systems also need an HMD to help deliver the imagery integral to creating an immersive virtual world. There are a number of different HMDs on the market at Read more…

Face Detection and Recognition : Comparison of Amazon, Microsoft Azure and IBM Watson

Face Detection and Recognition : Comparison of Amazon, Microsoft Azure and IBM Watson

  Face Detection and Recognition: Comparison of Amazon, Microsoft Azure and IBM Watson In today’s world, everybody wants readymade things. In case of face detection and face recognition, many industries provided so many powerful API’s which are ready to use. Here In this blog, we are going to discuss some of Read more…

Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras

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.

Entrance preparation tips

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