Adel Elmashad

Product Review Sentiment Analysis on Amazon Dataset

• Analyzed consumer product reviews using Python to extract insights on sentiment, themes, and

customer behavior patterns.

• Cleaned and processed raw JSON data, handling missing values and irrelevant fields to prepare

for analysis.

• Performed exploratory data analysis (EDA) on multiple products to uncover trends in ratings,

review timing, and word usage.

• Applied Natural Language Processing (NLP) techniques such as tokenization, stop-word

removal, stemming, and lemmatization to analyze review text.

Stock Market Trend Prediction Using Machine Learning

• Analyzed historical stock market data to identify patterns and predict future price movements.
• Collected and processed time-series data, handling missing values and outliers for accurate modeling.
• Conducted exploratory data analysis (EDA) to uncover correlations, volatility trends, and seasonal effects.
• Engineered features such as moving averages, RSI, and volatility indicators to improve predictive power.
• Implemented and compared machine learning models (e.g., Linear Regression, Random Forest, LSTM) to forecast market trends.
• Evaluated model performance using metrics like RMSE, MAE, and accuracy, optimizing hyperparameters for better predictions.