Auto-Forecast

Framework

Problem

Nowadays there is an urgent need for forecasting automatisms with near real-time frequency.
It is required In any industrial context, not only finance, but e.g. IOT for making prevention.

Humanativa – Tools and Expertise

Auto-Forecast Module in the TimeSeries context

  • For the EDA (Exploratory Data Analysis) phase, introduces deep data analysis techniques over time
  • for the Model Production phase, introduces an Auto-Forecast engine that exploits the results of the analysis of the EDA phase to automatically define a protocol for the production of an efficient model.
  • For the MLOps phase: to automatically replicate Model and Pipeline in various MLOps environments in the Cloud to prepare for Production.

Benefits

  • Decreased EDA time
  • Decrease in Learning Time
  • Decrease in re-training time (MLOps)

Use Case

  • Industry: Banking
    Use case: Customer insight per Up e Cross selling – Forecast
  • Industry: Automotive – Smartcity
    Use case: Vehicle Flow forecast & Behavioural profiling
  • Industry: AIR Transportation – IOT
    Use case: Passenger Flow Forecast