Preprocessing text based with nlp technique

This project, part of my PGP in AI & ML from Great Learning, analyzes stock market news sentiment and summarizes key insights using NLP techniques. It includes text preprocessing, word embeddings, and sentiment-based stock price movement prediction. Tools: Python, NLTK, Transformers, Gensim, Sentence Transformers

This project, part of my PGP in AI & ML from Great Learning, explores clustering techniques like K-Means and hierarchical clustering. Includes feature preprocessing, dimensionality reduction, and cluster evaluation. Tools: Python, Scikit-Learn, Yellowbrick, Pandas, Seaborn

This project, completed as part of my PGP in AI & ML from Great Learning, explores supervised learning techniques like Decision Trees, Random Forest, SVM, and Logistic Regression. Includes data preprocessing, model training, evaluation, and hyperparameter tuning. Tools: Python, Scikit-Learn, Pandas, Matplotlib.

This project predicts whether a loan applicant is likely to default using machine learning models. It includes data preprocessing, feature engineering, model training (Logistic Regression, Decision Tree), and performance evaluation. Built as part of my PGP in AI/ML program to simulate real-world financial risk assessment.