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Analysis on data declared by each candidates in their affidavits submission Election Commission.

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Loksabha Election Case Study

Advanced Machine Learning Analysis: Predicting Voting Percentage Based on Candidate Credentials

Pleased to present an advanced machine-learning exercise dedicated to predicting voting percentages based on a candidate's credentials.

Key Components:

Data Processing and Model Development:

Explore the foundational stages of our analysis, including meticulous data crawling, precise data acquisition, and rigorous data labeling. Witness the expertise of our machine learning model training, ensuring the highest standards of accuracy and reliability. Detailed insights into these crucial aspects can be accessed here.

Predictor Service Implementation:

Discover our cutting-edge predictor service designed to forecast voting percentages with precision. This service, a culmination of extensive research and technical proficiency, offers invaluable insights into winnability predictions. For an in-depth understanding of our predictor service, please navigate to the following link: Predictor Service Repository.

We invite you to explore our work, symbolizing a harmonious application of data science for electoral analysis. Your interest in our research is highly appreciated, and we trust you will find our findings insightful and valuable.

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Analysis on data declared by each candidates in their affidavits submission Election Commission.

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