Why should we bother ?? Distributions plays a very crucial role in data science and analytics. Statistical distributions shows us the underlying relationship between the data points. The main purpose of checking distributions is to get an idea on how the data points of the target are spread across, so that appropriate model could be … Read more
https://appliedmachinelearning.blog/2020/01/22/introducing-finbert-embedding-pypi-bert-language-model-fine-tuned-on-financial-data This blog-post demonstrate the finbert-embedding pypi package which extracts token and sentence level embedding from FinBERT model (BERT language model fine-tuned on financial news articles). The finbert model was trained and open sourced by Dogu Tan Araci (University of Amsterdam). BERT, published by Google, is conceptually simple and empirically powerful as it obtained state-of-the-art results on … Read more
https://appliedmachinelearning.blog/2019/12/31/extractive-text-summarization-using-glove-vectors Text summarization is one of famous NLP application which had been researched a lot and still at its nascent stage compared to manual summarization. In simple terms, the objective is to condense unstructured text of an article into a summary automatically. There are two types of summarization techniques. Extractive Summarization Extractive summarization is extracting … Read more
Question answering system is a field of information retrieval and natural language processing which is concerned with building systems that automatically answer questions asked by a human. Ideally, the task would like a English reading comprehension task where given a passage or paragraph, system would be able to process texts, understand it and correctly answer … Read more
Problem Statement: To simply put, You have 1 million text files in a directory and your application must cater text query search on all files within few seconds (say ~1-2 seconds). How will you develop such system !!. Motivation: The idea came from my previous post “Performing OCR by running parallel instances of Tesseract 4.0 … Read more
his blog-post presents building a demonstration of emotion recognition from the detected bounded face in a real time video or images. Introduction An face emotion recognition system comprises of two step process i.e. face detection (bounded face) in image followed by emotion detection on the detected bounded face. The following two techniques are used for … Read more
Table of Contents HR Analytics : Hackathon Challenge I participated in WNS Analytics Wizard hackathon, “To predict whether an employee will be promoted or not” and hence I am coming up with this blog-post of the solution submitted which ranked me 138 (Top 11%) in the challenge. The leader board ranking was decided on the … Read more
Text classification is a problem where we have fixed set of classes/categories and any given text is assigned to one of these categories. In contrast, Text clustering is the task of grouping a set of unlabeled texts in such a way that texts in the same group (called a cluster) are more similar to each other than to those in other … Read more
Much recently, I built a system for pursuing deep learning (DL) exercises. Let me give a heads-up that it is purely based on requirement or use cases on what one wants to achieve. For example: I am not a big fan of cloud based DL as it is expensive if you are using it for … Read more
This blog-post is the subsequent part of my previous blog-post on developing question answering system on Facebook bAbI data-set. In my previous article, I described the bAbI data-set and we have extracted features for building the model. If you have directly landed on this blog-post then I would suggest you to read the previous Developing factoid question answering … Read more
