What is Transfer Learning? – A Simple Introduction.
Transfer Learning is a technique in machine learning where we reuse a pre-trained model to solve a different but related problem. It is one of the popular methods to train...
What is UNET?
UNET is an architecture developed by Olaf Ronneberger and his team at the University of Freiburg in 2015 for biomedical image segmentation. It is a highly popular approach for semantic...
Data Augmentation for Semantic Segmentation – Deep Learning
All the technological advancements in the field of Artificial Intelligence (AI) is facilitated due to the availability large amount of dataset and the computational hardware’s like GPU’s and TPU’s. In...
DCGAN – Implementing Deep Convolutional Generative Adversarial Network in TensorFlow
In this tutorial, we are going to implement a Deep Convolutional Generative Adversarial Network (DCGAN) on Anime faces dataset. The code is written in TensorFlow 2.2 and Python3.8 . According...
GAN – What is Generative Adversarial Network?
Generative Adversarial Network or GAN is a machine learning approach used for generative modelling designed by Ian Goodfellow and his colleagues in 2014. It is made of two neural networks:...
What is Data Augmentation?
Data augmentation is a process that enables you to increase the amount of training data by making reasonable modifications in your existing data. It helps you to increase the diversity...
What is Deep Learning
Currently, Artificial Intelligence (AI) is progressing at a great pace and deep learning is one of the main reasons for this, so all the people need to get a basic...