This template depicts a data analysis and machine learning workflow diagram, which thoroughly demonstrates the complete process from a dataset to detection of accuracies. It starts with a dataset, encompassing steps of exploratory data analysis and data preprocessing including splitting, noise removal, normalization, followed by model selection and predictive modeling. Specifically, it involves steps like vocabulary lookup, token id mapping, and feature hashing, concluding with the examination of model performance through the detection of accuracies. This workflow diagram is immensely useful for data scientists, machine learning engineers, and any professionals concerned with data analysis workflows, as it helps them plan and execute efficient data processing and analysis strategies.
