In this post, we will show you how to use VibeVoice Text to Speech AI from Microsoft. VibeVoice is a next-generation text-to-speech (TTS) AI framework that converts written text into natural, ...

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements. The mechanism relies on visual ...

In this video, we will understand what is Keras and Tensorflow. Tensorflow is a free and open-source library for machine learning and artificial intelligence. It was developed by Google. And it can be ...

If old sci-fi shows are anything to go by, we're all using our computers wrong. We're still typing with our fingers, like cave people, instead of talking out loud the way the future was supposed to be ...

Abstract: This paper presents an application for troubleshooting computer problems using the TensorFlow and deep learning techniques. The functionality of the proposed application contains the problem ...

TensorFlow was created simply to develop your own machine-learning (ML) models. You might even experience it daily and not know it, like recommendation systems that suggest the next YouTube video, ...

Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.

CIFAR-10 image classification using TensorFlow/Keras with a custom F-Beta metric. Includes CNN architecture, data preprocessing, EarlyStopping, and performance tracking to balance precision and recall ...

Implementation of multiple deep learning models using Keras Functional API, including a CNN on MNIST, a multi-input/multi-output example, and a toy ResNet on CIFAR-10 ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

In addition, many short text classification methods, in particular, deep neural network approaches, require a large amount of annotated data, which, as described previously, is often not possible or ...

Abstract: Classification of birds is of significant importance when it comes to assessment of biological diversity, or the identification of ecosystems that are most threatened. The conventional ...