What is Data Science: Lifecycle, Applications, Prerequisites, and Tools
Data Science is a field that involves the extraction of knowledge and insights from large and complex data sets. It involves a combination of statistical analysis, machine learning, and data visualization techniques to transform raw data into meaningful information.
Lifecycle:
The Data Science lifecycle typically involves the following steps:
Problem Formulation: Identifying the business problem or question to be answered through data analysis.
Data Collection: Gathering relevant data from various sources.
Data Preparation: Cleaning, transforming, and processing the data for analysis.
Data Exploration: Analyzing and visualizing the data to identify patterns and trends.
Data Modeling: Developing predictive models and algorithms based on the data.
Model Evaluation: Assessing the performance of the model and fine-tuning it as necessary.
Deployment: Implementing the model into a production environment and using it to make predictions or inform decision-making.