Data Processing

This engine collects raw data and translates into usable information. It uses a single endpoint architecture, differentiated by function codes.

Below are the specific function codes for functionality

Data Input

Specify the data sources, this functionality can take database connection or CSV file or JSON file

Data Input (DP_1)

Missing Data

This functionality handles missing data using various techniques. e.g mean, mode and more

Missing Data (DP_2)

Data Encoding

This functionality converts data to a recognizable format through encoding. Supported techniques include one-hot, label and categorical encoding.

Data Encoding (DP_3)

Data Split

This functionality splits data into two subsets: a training set and a test set. The training set is used to train a model, while the test set is used to evaluate its performance.

Data Split (DP_4)

Feature Scaling

This functionality normalizes the range of values for different features in the dataset.

Feature Scaling (DP_5)

Drop Data Column

This functionality drops specified multiple columns on the X and Y columns.

Drop Columns (DP_6)

Time Stepper

This functionality enables you to transform your data into a time series format.

Time Stepper (DP_7)

Good to know: Using the 'Page Link' block lets you link directly to a page. If this page's name, URL or parent location changes, the reference will be kept up to date. You can also mention a page – like – if you don't w/sant a block-level link.