Projects:

GenAI, NLP and LLM for Customer Support Ticket Classification Github: Used methods and Skills: Python, TensorFlow/Keras, Scikit-Learn, NLP libraries (like NLTK spaCy)

Computer Vision for Plant Seedling Classification Build a Convolutional Neural Netowrk to classify plant seedlings into their respective categories. create a classifier capable of determining a plant's species from an image Github: Used methods and Skills: Image Processing, Keras, Tensorflow, Convolutional Neural Networks, Transfer Learning

Bank Customer Churn Prediction Analyze the customer data, build a neural network to help the operations team identify the customers that are more likely to churn, and provide recommendations on how to retain such customers Github: Used methods and Skills: EDA, Data Preprocessing, Tensorflow, Keras, Artificial Neural Networks, Regularization

Credit Card Users Churn Prediction Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it Github: Used Methods and Skills: EDA, Random Forest, Bagging, Boosting, SMOTE, Cross Validation, Data Preprocessing, Hyperparameter Tuning, Ensemble Techniques

Personal Loan Campaign Modelling Analyze the data provided and build a predictive model that will help to identify the customers of a bank who have a higher probability of purchasing a loan Github: Used Methods and Skills: EDA, Data Preprocessing, Missing Value Treatment, Decision Trees, Pruning, Business Recommendations

FoodHub Perform an exploratory data analysis and provide actionable insights for a food aggregator company to get a fair idea about the demand of different restaurants and cuisines, which will help them enhance their customer experience and improve the business Used Methods and Skills: Python, Numpy, Pandas, Seaborn, Univariate analysis, Bivariate analysis, Exploratory Data Analysis, Business Recommendations