When considering the Data Science Life Cycle, which step involves assessing the performance of your model and ensuring it meets the project's objectives?
- Data Collection
- Data Preprocessing
- Model Building and Training
- Model Evaluation and Deployment
Model Evaluation and Deployment is the phase where you assess the performance of your data model and ensure it meets the project's objectives. During this step, you use various metrics and techniques to evaluate how well the model is performing and decide whether it's ready for deployment. This phase is crucial for ensuring that the data-driven solution is effective and meets the desired outcomes.
Loading...
Related Quiz
- In MongoDB, the _______ operator can be used to test a regular expression against a string.
- How does transfer learning primarily benefit deep learning models in terms of training time and data requirements?
- For applications requiring ACID transactions across multiple documents or tables, which database type would you lean towards?
- Which of the following is not typically a layer in a CNN?
- Which database system is based on the wide-column store model and is designed for distributed data storage?