Articles About Natural Language Processing

October 31, 2020 Advanced, Algorithm, Computer Vision, Deep Learning, NLP, Python, Unstructured Data Leave a comment

A Comprehensive Guide to Attention Mechanism in Deep Learning for Everyone

Overview The attention mechanism has changed the way we work with deep learning algorithms Fields like Natural Language Processing (NLP) and even Computer Vision have been revolutionized by the attention mechanism We will learn how this attention mechanism works in deep learning, and even implement it in Python Introduction “Every once in a while, a revolutionary product comes along that changes everything.” – Steve Jobs What does one of the most famous quotes of the 21st century have to do with […]

October 31, 2020 Intermediate, NLP, Python, Technique, Unsupervised, Word Embeddings Leave a comment

An Essential Guide to Pretrained Word Embeddings for NLP Practitioners

Overview Understand the importance of pretrained word embeddings Learn about the two popular types of pretrained word embeddings – Word2Vec and GloVe Compare the performance of pretrained word embeddings and learning embeddings from scratch Introduction How do we make machines understand text data? We know that machines are supremely adept at dealing and working with numerical data but they become sputtering instruments if we feed raw text data to them. The idea is to create a representation of words […]

October 31, 2020 Beginner, NLP, Python, Technique, Unstructured Data Leave a comment

How Part-of-Speech Tag, Dependency and Constituency Parsing Aid In Understanding Text Data?

Overview Learn about Part-of-Speech (POS) Tagging, Understand Dependency Parsing and Constituency Parsing Introduction Knowledge of languages is the doorway to wisdom. – Roger Bacon I was amazed that Roger Bacon gave the above quote in the 13th century, and it still holds, Isn’t it? I am sure that […]

October 31, 2020 Advanced, Classification, NLP, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

Simple Text Multi Classification Task Using Keras BERT

This article was published as a part of the Data Science Blogathon. Introduction BERT is a really powerful language representation model that has been a big milestone in the field of NLP. It has greatly increased our capacity to do transfer learning in NLP. It comes with great promise to solve a wide variety of NLP tasks. Definitely you will gain great knowledge by the end of this article, keep reading. I am sure you will get good hands-on experience […]

October 30, 2020 NLP, non-autoregressive NMT

Issue #105 – Improving Non-autoregressive Neural Machine Translation with Monolingual Data

30 Oct20 Issue #105 – Improving Non-autoregressive Neural Machine Translation with Monolingual Data Author: Dr. Chao-Hong Liu, Machine Translation Scientist @ Iconic Introduction In the training of neural machine translation (NMT) systems, determining how to take advantage of monolingual data and improve the performance of the resulting trained models is a challenge. In this post, we review an approach proposed by Zhou and Keung (2020), under the framework of non-autoregressive (NAR) NMT. The results confirm that NAR models achieve better […]

October 29, 2020 Big data, Business Analytics, Intermediate, NLP, R, Technique, Text, Unstructured Data Leave a comment

Hacks to perform faster Text Mining in R

Introduction Data science demands versatility. Move away from your regular methods, challenge your ways of working, explore new ways of doing things more efficiently. On reminiscing about my old days, my initial years in data science, I had also got trapped by this devil of ‘complacency’. At one point, I was not challenging myself enough. I wasn’t experimenting with the ways of doing work. I accepted the things as they were, until I realized ‘Complacency is a state of mind […]

October 29, 2020 Beginner, Business Intelligence, NLP, Use Cases Leave a comment

How to leverage Social Media Analytics for your business?

Introduction Conventional media, such as television, radio or newspapers transmits information only in one direction. Users can consume the information which the media offers, but they have very little or no ability to share their own views on the subject. Now-a-days, digital mediums has made it possible to have a two-way form of communication that allows individuals to interact with the information being transmitted. This is known as Social media which encompasses a wide variety of online content, from social […]

October 29, 2020 Clustering, Libraries, Machine Learning, NLP, Programming, Python, Technique, Text, Unstructured Data, Unsupervised Leave a comment

Introductory guide to Information Retrieval using kNN and KDTree

Introduction I love cricket as much as I love data science. A few years back (on 16 November 2013 to be precise), my favorite cricketer – Sachin Tendulkar retired from International Cricket. I spent that entire day reading articles and blogs about him on the web. By the end of the day, I had read close to 50 articles about him. Interestingly, while I was reading these articles – none of the websites suggested me articles outside of Sachin or cricket. […]

October 29, 2020 Deep Learning, Image, NLP, Project, Python, PyTorch, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

Automatic Image Captioning using Deep Learning (CNN and LSTM) in PyTorch

Introduction Deep Learning is a very rampant field right now – with so many applications coming out day by day. And the best way to get deeper into Deep Learning is to get hands-on with it. Take up as much projects as you can, and try to do them on your own. This would help you grasp the topics in more depth and assist you in becoming a better Deep Learning practitioner. In this article, we will take a look […]

October 29, 2020 Intermediate, NLP, Podcast, Research & Technology Leave a comment

DataHack Radio #12: Exploring the Nuts and Bolts of Natural Language Processing with Sebastian Ruder

https://soundcloud.com/datahack-radio/episode-12-sebastian-ruder Introduction There’s text everywhere around us, from digital sources like social media to physical objects like books and print media. The amount of text data being generated every day is mind boggling and yet we’re not even close to harnessing the full power of natural language processing. I see a ton of aspiring data scientists interested in this field, but they often turn away daunted by the challenges NLP presents. It’s such a niche line of work, and we […]

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