What Is Data Science?

Data Science is an interdisciplinary field that focuses on extracting meaningful insights from structured and unstructured data. It combines concepts from statistics, mathematics, computer science, and domain knowledge to analyze data and support decision-making.

A typical data science workflow includes data collection, data cleaning, exploratory data analysis, feature engineering, model building, and result interpretation. These steps help transform raw data into useful information.

Machine Learning plays a crucial role within Data Science. ML algorithms learn patterns from historical data and use those patterns to make predictions or recommendations without being explicitly programmed.

In this project, Machine Learning is used to analyze movie data and automatically recommend similar movies to users based on genre patterns and user rating behavior. This makes the Movie Recommendation System a practical application of Data Science using Machine Learning techniques.

Key Features of Data Science:

• Data Collection and Cleaning: Gathering raw data from multiple sources and preparing it for analysis.
• Exploratory Data Analysis (EDA): Understanding patterns, trends, and distributions in the data.
• Feature Engineering: Converting raw data into meaningful features for models.
• Machine Learning Integration: Applying ML algorithms to learn from data and make predictions.
• Insight Generation: Interpreting results to support data-driven decisions.