Data Science

Introduction : Projects focused on data analysis, visualization, and deriving insights without heavy ML models.

Project Title : Google Play Store Analysis

Statement : Analyze app ratings, downloads, and user sentiments.

Approach : Cleaned and visualized data using descriptive statistics and sentiment analysis.

Tools : Python (Pandas, Matplotlib), Power BI.

Project Title : Breath Alcohol Test Data Analysis

Statement : Study trends in alcohol-related incidents from 2013–2017.

Approach : Performed time-series analysis and clustering.

Tools : Python, R, Tableau.

Project Title : Medical Diagnosis Prediction (Chatbot)

Statement : Assist in diagnosing conditions using symptom data.

Approach : Built a rule-based system with basic ML for pattern recognition.

Tools : Python, Flask, SQLite.

Project Title : Sales Forecasting for E-commerce

Statement : Predict sales trends using historical data.

Approach : Applied ARIMA and LSTM for time-series forecasting.

Tools : Python, AWS Sagemaker, Excel.

Project Title : LEGO Set Analysis

Statement : Explore LEGO themes, colors, and parts over time.

Approach : Cleaned and visualized datasets using clustering and regression.

Tools : Python, Tableau, Jupyter Notebook.

Project Title : Social Media Sentiment Analysis

Project Statement: Analyze sentiment in social media posts.

Approach: Use NLP to process text data and classify sentiment.

Tools & Technology: Python, NLTK, SpaCy, Matplotlib.

Project Title : Retail Sales Forecasting

Project Statement : Predict future sales for retail businesses.

Approach : Use time-series forecasting models like ARIMA and Prophet.

Tools & Technology : Python, Pandas, Prophet, Matplotlib.