MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Step 2: Data Cleaning Next, this data flows to the cleaning step. To make sure the data paints a consistent picture that your pipeline can learn from, Cortex automatically detects and scrubs away outliers, missing values, duplicates, and other errors.

Detailed explanation-2: -A machine learning pipeline is a way to codify and automate the workflow it takes to produce a machine learning model. Machine learning pipelines consist of multiple sequential steps that do everything from data extraction and preprocessing to model training and deployment.

Detailed explanation-3: -A typical workflow consists of Ingestion, Data cleaning, Data pre-processing, Modelling, and deployment. In ML workflow, all these steps are run together with the same script. It means the same script will be used to extract data, clean data, model, and deploy.

Detailed explanation-4: -Evaluation At this stage, you should have a trained model and are ready to conduct evaluation techniques on its performance. For evaluation, we utilize a partition of the refined data, usually referred to as the ‘test data’. The test data have not been seen during the model during training.