April 23, 2021 Beginner, Deep Learning, NLP

Role of Machine Learning in Natural Language Processing

Introduction Machine Learning and Natural Language Processing are important subfields of Artificial Intelligence that have gained prominence in recent times. Machine Learning and Natural Language Processing play a very important part in making an artificial agent into an artificial ‘intelligent’ agent. An Artificially Intelligent system can accept better information from the environment and can act on the environment in a user-friendly manner because of the advancement in Natural Language Processing. Similarly, an Artificially Intelligent System can process the received information […]

March 11, 2021 Advanced, NLP, Supervised, Text, Unstructured Data Leave a comment

A Hands-On Introduction to Hugging Face’s AutoNLP 101

Hugging Face, founded in 2016, has revolutionized the way people approach Natural Language Processing in this day and age. Based in New York, Hugging Face started out as a chatbot company with its primary focus today on the Transformers library and helping the developers integrate NLP into their own products or services. Hugging Face has made it incredibly easy for an individual to train their data on huge state-of-the-art models only with a couple of lines. Solving NLP, one commit […]

December 21, 2020 Deep Learning, NLP, Semi-supervised, Word Embeddings Leave a comment

Multilingualism in Natural Language Processing: Targeting Low Resource Indian Languages

Introduction A language is a systematic form of communication that can take a variety of forms. There are approximately 7,000 languages believed to be spoken across the globe. Despite this diversity, the majority of the world’s population speaks only a fraction of these languages. In Spite of such a rich diversity Languages are still evolving across time much like the society we live in. While the English language is uniform, having the distinct status of being the official language of […]

December 20, 2020 Deep Learning, NLP, Semi-supervised, Uncategorized, Word Embeddings Leave a comment

Multilingualism in Natural Language Processing targeting low resource Indian languages

Introduction Language is a systematic form of communication that can take a variety of forms. There are approximately 7,000 languages believed to be spoken across the globe. Despite this diversity, the majority of the world’s population speaks only a fraction of these languages. In Spite of such a rich diversity Languages are still evolving across time much like the society we live in. While the English language is uniform, having the distinct status of being the official language of multiple […]

December 18, 2020 Python

Spelling Correction in Python with TextBlob

Introduction Spelling mistakes are common, and most people are used to software indicating if a mistake was made. From autocorrect on our phones, to red underlining in text editors, spell checking is an essential feature for many different products. The first program to implement spell checking was written in 1971 for the DEC PDP-10. Called SPELL, it was capable of performing only simple comparisons of words and detecting one or two letter differences. As hardware and software advanced, so have […]

December 15, 2020 Computer Vision, Datasets, Deep Learning, Intermediate, Listicle, Machine Learning, NLP, Project Leave a comment

Top 15 Open-Source Datasets of 2020 that every Data Scientist Should add to their Portfolio!

Overview Here is a list of Top 15 Datasets for 2020 that we feel every data scientist should practice on The article contains 5 datasets each for machine learning, computer vision, and NLP By no means is this list exhaustive. Feel free to add other datasets in the comments below Introduction For the things we have to learn before we can do them, we learn by doing them -Aristotle I am sure everyone can attest to this saying. No […]

December 3, 2020 Python

Simple NLP in Python with TextBlob: N-Grams Detection

Introduction The constant growth of data on the Internet creates a demand for a tool that could process textual information in a faster way with no effort from the ordinary user. Moreover, it’s highly important that this instrument of text analysis could implement solutions for both low and high-level NLP tasks such as counting word frequencies, calculating sentiment analysis of the texts or detecting patterns in relationships between words. TextBlob is a great lightweight library for a wide variety of […]

December 2, 2020 Analytics Vidhya, Classification, Data Science, Intermediate, Libraries, NLP, Programming, Python, Supervised, Text, Unstructured Data Leave a comment

Step by step guide to building sentiment analysis model using graphlab

I have been using graph lab for quite some time now. The first Kaggle competition I used it for was Click Trough Rate (CTR) and I was amazed to see the speed at which it can crunch such big data. Over last few months, I have realised much broader applications of GraphLab. In this article I will take up the text mining capability of GraphLab and solve one of the Kaggle problems. I will be referring to this problem with […]

December 2, 2020 Intermediate, Libraries, Machine Learning, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Natural Language Processing Made Easy – using SpaCy (in Python)

Introduction Natural Language Processing is one of the principal areas of Artificial Intelligence. NLP plays a critical role in many intelligent applications such as automated chat bots, article summarizers, multi-lingual translation and opinion identification from data. Every industry which exploits NLP to make sense of unstructured text data, not just demands accuracy, but also swiftness in obtaining results. Natural Language Processing is a capacious field, some of the tasks in nlp are – text classification, entity detection, machine translation, question […]

December 2, 2020 Intermediate, NLP, Project, Python, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

Building a FAQ Chatbot in Python – The Future of Information Searching

Introduction What do we do when we need any information? Simple: “We Ask, and Google Tells”. But if the answer depends on multiple variables, then the existing Ask-Tell model tends to sputter. State of the art search engines usually cannot handle such requests. We would have to search for information available in bits and pieces and then try to filter and assemble relevant parts together. Sounds time consuming, doesn’t it? Source: Inbenta This Ask-Tell model is evolving rapidly with the […]

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