Welcome
User Guide
Model Training
Data Upload
Data upload tab is used to load the dataset in the GUI to train the model and get insight of it.
Uploading External Data Sources
Users can also access data from external databases for model training.

Release Notes
Installation Guide
Developer Guide
MLAC User Guide
User Guide
- Introduction
  Marketing AION (Artificial Intelligence ON) is an AI life cycle management platform for applying machine learning to real-world problems. Marketing AION encompasses the complete pipeline from raw data ingestion to a deployable machine learning model with a less-code/no-code approach.
- Model Management
- Model Training
  - Data Upload
    Data upload tab is used to load the dataset in the GUI to train the model and get insight of it.
    - Uploading Data File
      To upload the data file, complete the following steps:
    - Uploading a Document
      This option is used to upload a document.
    - Uploading a Python Script
      The python script needs to be created by the user, which can be converted into a data file.
    - Uploading External Data Sources
      Users can also access data from external databases for model training.
    - Uploading SKLearn Dataset
      To upload a standard sklearn data set, complete the following steps:
    - Using EDA
      EDA stands for Exploratory Data Analysis where user can analyze and investigate data sets and summarize their main characteristics, employing data visualization methods.
  - Basic Configuration
    This section provides the option to select more than one algorithm based on problem type and also provides the option to discard the unnecessary features from the dataset.
  - Updating Advanced Configuration
    To update the Advanced Configuration, complete the following steps:
  - Training the Model
    Model training tab gives the information about the Problem type, Selected algorithms, number of rows and Training Features, Training Data, Data balancing and Number of iterations.
- Model Prediction
  Model prediction predicts the input data based on the pattern of training data.
- Trusted AI
  This feature is available for classification and regression problem types.
- Model Monitoring
  This feature is available for classification and regression problem types.
- Utility
  For Data Generator and BYOM (Bring Your Own Model), select the Utility tab.

Uploading External Data Sources

Users can also access data from external databases for model training.

About this task

For uploading external data sources, complete the following steps:

Procedure

Click the Data Upload tab.
Click External Data Sources.
Select different SQL databases and data warehouses to ingest data. For example, SQLite, Microsoft SQL, PostgreSQL, MySQL, Oracle, Google BigQuery, Redshift, Snowflake, Actian.
To access data from the database, you need to provide essential credentials like Database Name, Username, Host Port, etc.
If a single table contains all the data, you can simply put the table name and fetch the table as Data Frame. Otherwise, the user can perform join and selection based on the condition to merge more than one table and finally fetch the data.

Note: Currently, this option is to upload data from some external databases and some data warehouses like- SQLite, PostgreSQL, etc. Users can insert a single table as a database. Also, some basic SQL operation like join, and selection based on where is also possible on multiple tables. Please contact Unica Admin to enable this option.

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