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Sentiment Analysis is a sub-field of Natural Language Processing. It is used to analyze or extract the true underlying meaning from texts, which can be anything from reviews to surveys and from customer feedbacks to tweets. Majorly, it classifies the text into positive, negative, or neutral sentiments.

For examples, if a customer writes a review for a particular product on Amazon, “Product received is not the Black Logo design pictured on the website. Unfortunately received the White Logo on Black cap instead which I definitely didn’t order from the seller.” A sentiment analysis model would correctly determine it is negative.

An easy guide for data analysis and visualization using Pandas and Seaborn.

Photo by Isaac Smith on Unsplash

I clearly remember my first class of Business Analytics as a grad student when the professor told us about how having the data is not enough, it is important to present it to people in a way they understand easily. And for explaining the data effortlessly to the audience, it is important for us to represent the data in a comprehensive way.

“By visualizing information, we turn it into a landscape that you can explore with your eyes. A sort of information map. And when you are lost in information, an information map is kind of useful.” — David McCandless


Artificial Intelligence (AI) or its subset Machine Learning (ML) is one of the most rapidly evolving field in the tech world . According to many surveys, AI and Machine Learning are the top technology trends in 2020. With high demand in these fields, more and more people are advancing their career in the field of Data Science and with plethora of courses and boot-camps available online, anyone can easily master the skills required to become a data science professional.

Artificial Intelligence is a branch of computer science where machines are designed or trained to performed activities which require intelligence. …

Anomita Chandra

An aspiring Data Science and Machine Learning enthusiast | Master's student |

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