Data-Analytics_Projects

• Exploratory Data Analysis Bollywood Movies & Cereal Ratings: The notebooks encompass detailed Exploratory Data Analysis (EDA) on two datasets—Bollywood Movies and Cereal Ratings—leveraging Python libraries such as NumPy and Pandas for data manipulation, SciPy for statistical analysis, and Matplotlib and Seaborn for advanced data visualization. The analysis includes techniques such as correlation analysis, distribution plotting, categorical comparisons, and outlier detection to extract actionable insights.
• Recommendation System: In this notebook, a Recommendation system is developed using Collaborative Filtering on the MovieLens dataset, relying on a user-item ratings matrix. The system applies neighborhood-based methods and computes pairwise user similarity scores to infer latent preferences and deliver content-personalized movie suggestions.