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 Post-independence poetry themes The post-independence poetry underwent a sea change as far as the themes are concerned. The poets are faced with the crisis of identity so their poetry is one of quest, a search of their self, a search for their cultural roots. The reason for such a theme of Indian poetry is not far to seek. The Indian poets who express themselves in English have their cultural roots in their community. Many of these Indian poets have been educated abroad but since they belong to the middle - class, they find themselves alienated within their own immediate circle and even from the westernized ethos. Some of the poets come from different racial backgrounds but are nationals of India for example, Nissim Ezekiel is a Jew, Dom Moraes is an Anglo Indian, Daruwalla and Jussawalla are Parsees, Eunice De Souza is a Goan Christian. The Indian poet writing in English therefore finds himself alienated. So the poetry of modern Indian poets naturally turns on the theme of identity c

  What is an artificial neural network? Here’s everything you need to know Michael Tyka If you’ve spent any time reading about  artificial intelligence , you’ll almost certainly have heard about artificial neural networks. But what exactly is one? Rather than enrolling in a comprehensive computer science course or delving into some of the more in-depth resources that are available online, check out our handy layperson’s guide to get a quick and easy introduction to this amazing form of machine learning. What is an artificial neural network? Artificial neural networks are one of the main tools used in machine learning. As the “neural” part of their name suggests, they are brain-inspired systems which are intended to replicate the way that we humans learn. Neural networks consist of input and output layers, as well as (in most cases) a hidden layer consisting of units that transform the input into something that the output layer can use. They are excellent tools for finding patterns whic

  What is a convolutional neural network, exactly? Well, let’s start with the basics: a convolutional neural network (CNN) is a type of neural network that is most often applied to image processing problems. You’ve probably seen them in action anywhere a computer is identifying objects in an image. But you can also use convolutional neural networks in natural language processing projects, too. The fact that they are useful for these fast growing areas is one of the main reasons they’re so important in deep learning and artificial intelligence today. What makes a convolutional neural network unique? Once you understand how a convolutional neural network works and what makes it unique from other neural networks, you can see why they’re so effective for processing and classifying images. But let’s first take a regular neural network. A regular neural network has an input layer, hidden layers and an output layer. The input layer accepts inputs in different forms, while the hidden layers pe

  Want to know how Deep Learning works? Here’s a quick guide for everyone. by Radu Raicea Artificial Intelligence  (AI) and  Machine Learning  (ML) are some of the hottest topics right now. The term  “AI”  is thrown around casually every day. You hear aspiring developers saying they want to learn AI. You also hear executives saying they want to implement AI in their services. But quite often, many of these people don’t understand what AI is. Once you’ve read this article, you will understand the basics of AI and ML. More importantly, you will understand how  Deep Learning , the most popular type of ML, works. This guide is intended for everyone, so no advanced mathematics will be involved. Background The first step towards understanding how Deep Learning works is to grasp the differences between important terms. Artificial Intelligence  is the replication of human intelligence in computers. When AI research first started, researchers were trying to replicate human intelligence for spec

  An Introduction to Deep Learning During recent years, deep learning has become somewhat of a buzzword in the tech community. We always seem to hear about it in news regarding AI, and yet most people don’t actually know what it is! In this article, I’ll be demystifying the buzzword that is deep learning, and providing an intuition of how it works. Building the Intuition Generally speaking, deep learning is a machine learning method that takes in an input X, and uses it to predict an output of Y. As an example, given the stock prices of the past week as input, my deep learning algorithm will try to predict the stock price of the next day. Given a large dataset of input and output pairs, a deep learning algorithm will try to minimize the difference between its prediction and expected output. By doing this, it tries to learn the association/pattern between given inputs and outputs — this in turn allows a deep learning model to generalize to inputs that it hasn’t seen before. As another e