Restaurant-Data Data Exploration and Preprocessing,Descriptive Analysis,Geospatial Analysis,Table Booking and Online Delivery,Price Range Analysis,Feature Engineering
Data Collection: Gathering data from various sources (CSV file Dataset.csv).
Data Cleaning & Preprocessing: Removing errors, duplicates, and missing values.
Exploratory Data Analysis (EDA): Understanding data through visualization and summary statistics.
Model Building: Using machine learning or statistical models to make predictions or classifications.
Interpretation & Decision Making: Using results to make informed business or research decisions.
Tools & Technologies Used
1.Programming: Python
Libraries: Pandas, NumPy, Scikit-learn, TensorFlow
Visualization: Matplotlib, Seaborn, Power BI, Tableau.