This repository contains my notes, practices, and solutions for the Applied Data Science Course offered by Sharif University of Technology (EE-879). The content covers various data science concepts, hands-on exercises, and solutions to course assignments.
For more details about the course, visit the official course website: Applied Data Science - Sharif University of Technology, Spring 2025
The course covers the following key topics:
- 📚 Introduction to Pandas
- 🧹 Data Cleaning and Preprocessing
- 📊 Data Visualization
- ⚙️ Feature Engineering and Dimensionality Reduction
- 🎯 Different Problem Types and Accuracy Measures
- 📈 Regression Methods
- 🔍 Classification Methods
- 🌂 Multiclass/Multilabel Classification and Boosting
- 🧠 Neural Networks
- 🚀 Deep Learning
- 🖼️ Deep Learning Application: Image Classification
- 🤖 Generative AI
- 📉 Model Explainability and Imbalanced Data Problems
The following datasets are utilized in this repository:
- 🚗 Car Features and MSRP
- 🧠 Stroke Prediction
- 🏠 Ames Iowa Housing Data
- 🏨 Hotel Booking Demand
- 🥑 Avocado Prices
- Assignment 1: Kaggle mini tutorial for introduction to Pandas.
- Assignment 2:
- Exploratory Analysis and Data Cleaning on Stroke Prediction dataset.
- Kaggle mini tutorial for Data Cleaning.
- Assignment 3:
- Data Visualization on Hotel Booking Demand
- Kaggle mini tutorial for Data Visualization.
- Practice 1: Explore pandas features on Car Features and MSRP dataset.
- Notes → Summarized lecture notes & key concepts
- Practices → Hands-on coding exercises & projects
- Assignments → Solutions to course assignments
Stay tuned for continuous updates! 🚀