Deep Learning

Hierarchical Attention Network For Multilabel Classification (Detailed Case study)

Wed, 11 Sep 2019 by Pritish Jadhav, Mrunal Jadhav / Deep Learning

In many real-world data applications, often we encounter scenarios where each data point may belong to multiple classes. A multilabel classifier is trained to predict the K most likely classes among N possible classes. The article focuses on solving multi-label text classification problems using the Hierarchical Attention Network.

Training Classifier Using PyTorch - Detailed Example.

Wed, 26 Jun 2019 by Pritish Jadhav, Mrunal Jadhav / Deep Learning

As a part of "Getting Acquainted with Deep Learning Frameworks" series, in the article we shall explore Pytorch Library. Pytorch is a deep learning library developed by Facebook Researchers. The focus of this article will be to highlight the steps involved in training a multiclass classifier using Pytorch.

Deep Neural Network for Multiclass Classification Using Keras.

Wed, 19 Jun 2019 by Pritish Jadhav, Mrunal Jadhav / Deep Learning

Getting started with deep learning frameworks often involves a steep learning curve. This article is aimed at providing a gentle introduction to building DNN models with Keras which can be scaled and customized as per dataset. The focus will be on understanding the syntax and good practices involved in building a complex DNN model rather than achieving accuracy.

Product Classificatication Using Image and Text (Deep Learning)

Wed, 10 Oct 2018 by Pritish Jadhav, Mrunal Jadhav / Deep Learning

Image classification using deep learning and its applications has been proving its worth across business verticals.However, building an image centric AI product is often marred by Unavailability of large amounts of data, poor quality of images, etc. Often the metadata / textual data associated with these images are ignored. In this article, we shall try and build a DL model that can leverage image as well as textual data.