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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...

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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...

OpenAI GPT-3: The successor of OpenAI GPT-2 0

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...

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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...

Introduction to autoencoder 0

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...

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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...

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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....

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Review: One Model To Learn Them All

Recent advancement in the field of deep learning has enabled us to develop models that yield impressive results across various fields, from image classification, object detection, to speech recognition. However, developing the architecture for each problem is a challenge in itself. In this paper, the authors present a single deep...

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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 of your training data which is essential for developing a robust model. This then, generally speaking, improves the performance of...