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 some fields like medical imaging, the availability of huge amount of data is not possible, as it takes good amount Continue Reading
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 to Yann LeCun, the director of Facebook AI, GAN is the “most interesting idea in the last 10 years of Continue Reading
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: generator network and a discriminator network. The generator network learns to generate new examples, while the discriminator network tries to Continue Reading
UNET Segmentation with Pretrained MobileNetV2 as Encoder
In this tutorial, we are going to work on UNet segmentation and use it for biomedical image segmentation tasks. This time we are going to use pre-trained MobileNetV2 as the encoder for the UNet architecture. We are going to integrate the pre-trained MobileNetV2 with the UNet and have an efficient Continue Reading
An Introduction to Scraping Images With Python
The Internet is a rich source of data and information in the world that is easy to acquire. This data includes images, PDF, text, audio, and video. To acquire the data it is necessary to scrape it. In this tutorial, we are going to learn about scraping images with python Continue Reading
OpenAI GPT-3: The successor of OpenAI GPT-2
The research lab OpenAI has released a preprint arXiv paper, titled “Language Models are Few-Shot Learners” or OpenAI GPT-3, which is a continuation of their previous work entitled “Language Models are Unsupervised Multitask Learners” or GPT-2. As a recap. GPT-2 is a language model based on the transformer architecture with Continue Reading
Building Convolutional Autoencoder using TensorFlow 2.0
We are going to continue our journey on the autoencoders. In this article, we are going to build a convolutional autoencoder using the convolutional neural network (CNN) in TensorFlow 2.0. Let us first revise, what are autoencoders? Autoencoders are neural networks that attempt to mimic its input as closely as Continue Reading
Introduction to Autoencoders
In today’s article, we are going to discuss a neural network architecture called autoencoders. This article is aimed at Machine Learning and Deep Learning beginners who are interested in getting a brief understanding of the underlying concepts behind autoencoders. So let’s dive in and get familiar with the concept of Continue Reading
Polyp Segmentation using UNET in TensorFlow 2.0
In this tutorial, we will learn about how to perform polyp segmentation using deep learning, UNet architecture, OpenCV, and other libraries. We will use a polyp segmentation dataset to understand how semantic segmentation is applied to real-world data. In polyp segmentation, the images with polyp are given to a trained Continue Reading
File Transfer using TCP Socket in C
In this tutorial, you will learn how to perform a file (data) transfer over a TCP socket in the C programming language. You will see how a client reads the data from a text file sends it to the server and then saves the data back into a text file. Continue Reading