Artificial Intelligence and Machine Learning
Machine Learning:
Extracting Knowledge from Observation Series
Machine Learning derives models from data and observations, including sensor data, to address specific application problems. Intecs Engineering describes a process covering domain analysis, objective setting, data acquisition and processing, model development and validation.
Application domain study
Analyze the state of the art and the various solutions available in the literature.
Targeted strategy
Determine goals and define a success criterion to achieve results.
Data acquisition
Define the different data acquisition campaigns.
Creating the model
Select the Machine Learning algorithms to use for training.
Model validation
Evaluate the model’s results and identify the refinements needed to meet the defined objectives.
Data processing
Identify how to prepare and process data for machine learning.
USE CASE:
AIVisionPark
Smart solutions for Urban mobility