Saras kumar
@Ankitjha00Data Scientist | Working on Machine Learning & NLP projects Python | Scikit-learn | Data Analysis
Language Breakdown
Lines of code distribution across 31 owned repositories
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Repos
32
PRs
0
Growth
+18%
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Coding Streak
Contribution activity over the past year
Top Repositories
This project focuses on predicting insurance claims and detecting potential fraud using historical insurance data. It involves data preprocessing, exploratory data analysis, feature engineering, and machine learning modeling to identify patterns in policyholder claims.
The Movie Recommendation System is a data science project designed to suggest movies to users based on their preferences. It uses content-based filtering and similarity measures to recommend movies that are closely related to the movie selected by the user. This project showcases the practical application of Machine Learning,
This task focuses on data visualization to effectively communicate insights derived from the restaurant dataset. Various charts and plots are created to explore rating distributions, compare performance across cuisines and cities, and analyze relationships between features and the target variable.
This project analyzes customer preferences by studying the relationship between cuisine types, restaurant ratings, and customer votes. The objective is to identify popular cuisines and determine which cuisines consistently receive higher customer ratings. Using data analysis and visualization techniques, the project provides actionable insights to
This project focuses on predictive modeling to estimate a restaurant’s aggregate rating using available features. Multiple regression-based machine learning models were developed, evaluated, and compared to identify the most effective approach.
This task focuses on feature engineering, a critical step in improving data quality and machine learning performance. New features are derived from existing columns to enhance the dataset’s predictive power.
This task focuses on price range analysis to understand how restaurant pricing relates to customer ratings. By analyzing price categories, the project identifies common pricing trends and evaluates how price impacts average restaurant ratings.
This task analyzes restaurant service features, focusing on table booking and online delivery options. The goal is to understand how these services impact restaurant ratings and how their availability varies across different price ranges.
Open Source Impact
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