Business by its definition can be said as a group of activities which ensures the movement of goods, money or services across the market by the term called trade. We generally judge a successful business by the amount of money it circulates or the impact it makes on the market. …

In this blog, I am going to discuss Graph Neural Network and its variants. Let us start with what graph neural networks are and what are the areas in which it can be applied. The sequence in which we proceed further is as follows:


  1. Graph and its motivation
  2. Graph Convolutions
  3. Graph Attention Networks
  4. Gated Graph Neural Networks
  5. Graph AutoEncoders
  6. Graph SAGE
  7. History behind GCN

Graph and its motivation

As the deep learning era has progressed so far, we have many states of the art solutions for datasets like text, images, videos etc. Mostly those algorithms consist of MLPs, RNNs, CNNs, Transformers, etc., which work…

When the entire world was shaken by the terror of a pandemic, I got an obvious notification from the CEO of my company stating the mandatory policy of working from home. Now for a guy like me, who just does not know how to work from home, it was soul-shattering news. I was worried more about the gym and the ideas of inadvertently bulking my body started to haunt me. To support the claim, the entire country was locked down to prevent the spread of the virus. For the first two days, it seemed like a pleasing vacation season and…

With the surfeit of blogs on this page, I decided to add one more to the list today. We will be talking about various terms like AutoEncoders and Variational AutoEncoders and finally implementing the latter one. So, you may have heard about data compression, right? It means nothing but encrypting the data in some form which consumes less memory and is capable of restoring almost everything of it when required. Can we do it through machine learning? Obviously, we can and here comes the time when we discuss autoencoders. So, let us kick in with our new blog.

What is an AutoEncoder?

So AutoEncoder…

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Question Answering using BiDAF

digging into a BiDAF model

Question Answering has been a major area of work in Natural Language Processing. I will be discussing as well as implementing the key elements of a research paper which does significantly well on QA related problems. So, What do we do in Question Answering? We are given a context and a query is asked based on that context. The task of the model is to find an accurate answer to the problem. The answer may or may not be present in the context itself. If it is present, the task can be formulated as a classification problem and if it…

As everyone comes up with a resolution at the start of the year, I would be trying to be more infrequent in my blog postings😀. As it has been over a month, I thought of spilling some words here 😀. In this blog, we will be discussing about an interesting paper on Generating Sequences With Recurrent Neural Networks proposed by Alex Graves(DeepMind). I will also be implementing the paper using Tensorflow and Keras.

Problem Definition

The dataset here is in the form of mathematical representation of handwritten strokes. So a point in the stroke sequence is a vector of length=3. The first…

Praphul Singh

Deep Learning Engineer, Oracle, IIT Kanpur

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