Standard AI processes include:
- Data pre-processing to format the data
- transformation and normalize data depending on what area of the policy we will be working on.
- Applying labeling to encode and transform categorical variables into numerical variables based on the decision tree.
- Data splitting into training and testing data sets utilizing k-fold cross-validation.
- Application of event clustering tools depending on need such as including k-nearest neighbors (knn), RNN, or GAN’s based on a set hyperparameters or dynamic parametrization of the data.
- We also look to enrich your data pipeline, prediction and learning models with additional data we may receive from other applications.
- Multi-class classification modeling.
- Extensive hyperparameter tuning and model validation by evaluating the precision, recall and F1 before releasing the models into production.
- Optimization by running a learning cycle based on your requirements and data set.
Netwila provides a multi-modal Logistics and Supply Chain application to maximize efficiency and improve profitability
Problem: Low Cube utilization
A lot of companies are shipping air and packaging not products driving up costs and carbon emission.
Leverage our ANwork app to enable: Live load and cost monitoring. Increase cube utilization using our LOAD IoT option and Track load flow.