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Shubham Sharma's Projects

flight-price-prediction icon flight-price-prediction

This project is a predictive analysis of flight prices using regression analysis. The project is aimed at predicting flight prices and understanding the factors that influence pricing. The project includes importing the dataset, performing EDA, handling categorical data, feature selection, fitting the model using the Random Forest algorithm.

smile-recognition icon smile-recognition

Smile Classification is a deep learning project that uses ResNet50 for image classification. The project involves data preprocessing, defining the model architecture, compiling and training the model using transfer learning. The final model accurately classifies images into three categories: positive smile, negative smile, and not smile.

spam-classifier-nlp icon spam-classifier-nlp

This is a machine learning project that focuses on detecting spam messages from regular messages. The project includes data cleaning and preprocessing, creating a bag of words model, and training the model using the Naive Bayes classifier. The final accuracy of the model is 98.39%.

subsciption-model-on-bamboo-product- icon subsciption-model-on-bamboo-product-

Project aims to improve retention and performance of bamboo product subscription-based models. Insights from surveys, focus group sessions, and literature studies were used to offer solutions in communication, customer relationship management. Identified barriers o the bamboo product industry's growth must be addressed to promote sustainability.

twitter_sentiment_analysis icon twitter_sentiment_analysis

I have done some Natural Language Processing on the Twitter US Airline Sentiment Dataset, which contains data for over 14000 tweets. Then I have used several classifiers namely, Support Vector Machine, Multinomial Naive Bayes, Random Forest and Decision Trees to predict the sentiment of the tweet i.e. positive, negative or neutral.

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