GlobalData Tool: Data Science Studio

DSS is intended for users who want to perform forecasting and build & train machine learning models but may not have programming expertise. It is particularly well-suited for users who want to work with data science tasks using a GUI rather than writing code.

Data Science Studio

 

• For forecasting, DSS provides three starting points:

• Curve-fit methods, which are well-suited for data that follows a predictable pattern;
• Time-series models, which are well-suited for data that exhibits patterns over time;
• Bayesian Forecasting Technique, which is a custom method developed by GlobalData that is particularly well-suited for data with a high degree of uncertainty or that is influenced by a wide range of factors.

• For machine learning, DSS provides a single starting point: "Build your own model."

This starting point offers a consistent process for building and training machine learning models, regardless of the type of problem being solved (regression, classification, or text classification). It includes a range of algorithms and libraries, including scikit-learn and TensorFlow, that can be used to build and train machine learning models for these different types of problems.

GlobalData Explorer → Tools → Data ScienceStudio

• Data input: DSS allows users to upload data from .csv or .xlsx files.
• Forecasting: DSS includes tools for performing forecasting, allowing users to input data and specify forecasting parameters.
• Machine learning model building and training: DSS provides a range of tools and options for building and training machine learning models, including support for popular libraries like scikit-learn and TensorFlow.
• Output: DSS provides output options that allow users to view, download and save the results of their forecasting or machine learning models predictions