The Github repository with the code can be found here. The article will go over how to set this up. Estimated time: under 30 minutes.
Machine (Reading) Comprehension is the field of NLP where we teach machines to understand and answer questions using unstructured text.
In 2016, StanfordNLP put together the SQuAD (Stanford Question Answering Dataset) dataset which consisted of over 100,000 question answer pairs formulated from Wikipedia articles. The challenge was to train a machine learning model to answer questions based on a contextual document. …
Interested in learning more about Natural Language Processing? Here are a few areas to start exploring to develop your niche.
The goal of sentiment analysis is to classify a corpus based on sentiment. Online stores might use sentiment analysis to determine if a review was favorable, while researchers might use it to find popular sentiments towards certain subjects such as the upcoming election.
For instance, this review would be classified as being positive through sentiment analysis:
Everything was great. The store was clean, fresh and prices were reasonable. I would definitely come back.
Intent and Slot classification is the process…
Climate change is the change in the distribution of weather patterns. While man-made climate change is commonly accepted as science, there are also skeptics who believe otherwise.
By applying machine learning techniques to tweets discussing climate change, we can better understand the effect of sociopolitical changes on these different perspectives.
To do this, we need to gather relevant data and build a predictive model which will help us determine sentiments of incoming tweets.
Here is the link to the repository containing all of the code shared in this article.
Using the Tweepy library from Python, we retrieved all tweets containing…