🚀 Welcome to my Data Science Portfolio! This repository showcases a diverse collection of data analysis, machine learning, and NLP projects, covering various real-world applications. Each project is well-documented with exploratory data analysis (EDA), feature engineering, model building, and performance evaluation.
✔ Exploratory Data Analysis (EDA): Insights from structured and unstructured data using Pandas, NumPy, Matplotlib & Seaborn.
✔ Machine Learning Models: Supervised & Unsupervised learning (Regression, Classification, Clustering, Time-Series Forecasting).
✔ Deep Learning & NLP: Sentiment Analysis, Spam Detection, and Text Classification using TensorFlow & Scikit-Learn.
✔ Big Data & Business Intelligence: Projects related to finance, healthcare, marketing, and economic indicators.
✔ End-to-End Implementation: Data preprocessing, visualization, model selection, hyperparameter tuning, and evaluation.
🔸 Predictive Modeling: House Price Prediction, Stock Market Analysis, Credit Card Fraud Detection.
🔸 Natural Language Processing (NLP): IMDb Sentiment Analysis, SMS Spam Detection, Hotel Reviews Sentiment Prediction.
🔸 Unsupervised Learning: Customer Segmentation (Mall Customers), Movie Recommendation Engine.
🔸 Time-Series Forecasting: COVID-19 Prediction, TSA Flight Passenger Traffic, Animated Weather Graphs.
🔸 EDA & Visualization: IPL Data Analysis, World Happiness Report, Airbnb Pricing Analysis.
🔹 Languages: Python (Pandas, NumPy, Scikit-Learn, TensorFlow, NLTK, Matplotlib, Seaborn)
🔹 Tools: Jupyter Notebook, Google Colab, SQL, Tableau
🔹 Frameworks: Scikit-Learn, TensorFlow, Keras, Statsmodels
Each project contains:
✅ Dataset Overview – Description and source of the dataset.
✅ Data Preprocessing & Cleaning – Handling missing values, feature engineering.
✅ EDA & Visualization – Graphical insights into data trends.
✅ Model Building & Evaluation – Performance metrics and model comparisons.
🔗 Connect with Me on LinkedIn | ✉ Email: [g.ishan091@gmail.com]