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Sentiment Analysis using Text Based Classifiers

Data Science Basics, Elections2019, Real Use Cases

May 2, 2020

Elections 2019 Mood Classification with Text Based Classifiers — II

Motivation: The General Elections in India are scheduled to be held between April and May. The volume of data generated through news and social media is huge. What an intriguing project to take up as a data scientist! Data Science offers algorithms to analyze those text, audio, and video data to infer the nation’s sentiment before, during, and after the elections. The statistical analysis of information available from all sources can provide a deep insight […]

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Sentiment Analysis using Text-Based Classifiers

Elections2019, Real Use Cases, Time Series

May 2, 2020

Sentiment Classification for 2019 Elections using Text Based Classifiers — I

Introduction The General Elections in India are scheduled to be held between April and May to constitute the 17th Lok Sabha. The nation is eagerly following news channels and newspapers to understand who will win the majority. THe numbers and data being generated around this is through the roof. What an intriguing project to take up as a data scientist! You can analyze and predict public sentiments towards prominent parties using a variety of sources […]

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Sentiment Analysis 2019 Elections

Data Science Basics, Elections2019, Real Use Cases

May 2, 2020

Twitter Sentiment Analysis for the 2019 General Assembly Elections

Introduction Sentiment analysis has been predominantly used in data science for analysis of customer feedbacks on products and reviews. They are used to understand user ratings on different kinds of products, hospitality services like travel, hotel bookings. It has also become popular to analyse user tweets — positive, negative or neutral by crawling twitter through APIs. In this article, we talk about sentiment analysis of the upcoming Lokshobha Elections for Congress and BJP by crawling […]

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Boosting, Bagging and Stacking Elections2019

Data Science Basics, Elections2019, Real Use Cases

May 1, 2020

Boosting, Bagging and Stacking — A Comparative Analysis (2019 India Elections Case Study)

Motivation We are inching closer to one of the most anticipated events in India — the General Elections! Everyone is hooked to the latest news and developments (and trust me, there is something happening every single day). This is a great time to be a data scientist. Why? There is so much data being generated thanks to these developments. We can come up with tons of use cases — visualizing sentiments, predicting sentiments, building models […]

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Deep Learning Vs Deep Reinforcement Learning Algorithms in Retail Industry

Deep Learning, Retail

May 1, 2020

Deep Learning Vs Deep Reinforcement Learning Algorithms in Retail Industry — II

LSTM, Transfer, Federated Learning, Reinforcement, and Deep Reinforcement Learning Introduction In continuation to my previous blog, which discussed on the different use-cases of machine learning algorithms in retail industry, this blog highlights some of the recent advanced technological concepts like role of IoT, Federated learning and Reinforcement learning in the context of retail industry. This blog is structured as follows: The use of IoT in retail domain and how different ML algorithms and feature extraction strategies […]

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