Tensorflow Tutorials
This article explores the process of image segmentation using Tensorflow Hub. These images have been pre-trained on large semantic segmentation datasets.
This article discusses the working of Convolutional Neural Networks on depth for image classification along with diving deeper into the detailed operations of CNN.
In this post, we’ll learn how to implement a Convolutional Neural Network (CNN) from scratch using Keras. Here, we show a CNN architecture similar to the structure of VGG-16 but
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We’ll begin with the topic of linear regression. Since linear regression can be
t-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction techniques used to vizualize data. Continue reading to know more.
Deep Learning has already surpassed human-level performance on image recognition tasks. On the other hand, in unsupervised learning, Deep Neural networks like Generative Adversarial Networks ( GANs ) have been
Imagine you have an image or an audio file which you would like to transfer to a friend. Sending the raw format data could be time-consuming and potentially inefficient, especially
