Data Collection
Gather relevant data from various sources, including internal databases, external databases, spreadsheets, APIs, and more. Ensure the data collected is accurate, complete, and aligned with the defined objectives.
Data Cleaning and Preprocessing
Clean and preprocess the raw data to handle missing values, remove duplicates, correct errors, and format the data for analysis. This step ensures the quality and integrity of the data.
Data Exploration
Explore the data to understand its characteristics, distribution, and relationships between variables. Visualization tools and descriptive statistics can aid in uncovering patterns and insights.
Evaluation
Evaluate the performance of the models using appropriate metrics. This step helps in assessing how well the models are performing and whether they meet the defined objectives.
