Sentiment Analysis on Twitter Data, Conducted sentiment analysis on Twitter data to gauge emotional tone and public opinion., Collected and preprocessed tweet datasets using NLTK for tokenization, stemming, and stop word removal., Applied NLP tools such as spaCy and TextBlob to analyze sentiment, considering context and language nuances., Developed and evaluated machine learning models using scikit-learn, achieving high accuracy and precision. Predicting Credit Card Approvals, Developed a machine learning model to predict credit card approval decisions., Performed data preprocessing and feature engineering using Pandas and NumPy., Conducted exploratory data analysis and visualized results using Matplotlib and Seaborn., Trained and tested various algorithms, including logistic regression and random forests, achieving high accuracy.