Learning is my passion, so is the interaction of technology with product strategy.
@pranjalshukla98
Built a Netflix recommendation system using Python, leveraging NLP techniques and cosine similarity to provide personalized content recommendations based on user preferences and content features. Cleaned and processed data, implemented text vectorization, and built a function to recommend movies and TV shows, enhancing the user experience on the platform..
Processed a mixed Fake and True News dataset using text cleaning, TfidfVectorizer, and a Multinomial Naive Bayes Classifier. The resulting model demonstrated a high accuracy of 95.31%, showcasing the effectiveness of our approach in classifying news authenticity. This project underscores the importance of preprocessing and appropriate algorithm selection in accurate news classification
Through extensive data cleaning and analysis of a vast dataset comprising 5.8 million domestic flights, this project delved into flight delay and cancellation patterns. Employing Tableau dashboards, key insights were extracted to evaluate airline performance, dissect route-specific delays, and examine social media's influence on customer sentiments. The project's outcomes emphasize its role in informed decision-making within the aviation industry.
Developed a Decision Tree model for predicting credit default probability, utilizing demographic and payment history data. Evaluated model fairness, ethical considerations, and potential risks to ensure responsible implementation within an educational context. (98% accuracy; trained 30000 data points and tested 7500 data points.