Data Transformation
Transforming the data involves converting it into a suitable format for analysis. This can include:
- Normalization and Scaling: Adjusting values to a common scale.
- Encoding Categorical Variables: Converting categorical data into numerical form (e.g., one-hot encoding).
- Feature Engineering: Creating new features based on existing ones to better capture the underlying patterns.
How to Create a Dataset?
Creating a dataset is a foundational step in data science, machine learning, and various research fields. A well-constructed dataset can lead to valuable insights, accurate models, and effective decision-making. Here, we will explore the process of creating a dataset, covering everything from data collection to preparation and validation.
Steps to Create a Dataset can be summarised as follows:
How to Create Dataset : 10 Steps to Create Dataset
- Define the Objective
- Identify Data Sources
- Data Collection
- Data Cleaning
- Data Transformation
- Data Integration
- Data Validation
- Documentation
- Storage and Access
- Maintenance
Contact Us