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Innovations and Objectives
Innovations and Objectives
Objectives
IML4E innovations
Results
Results
IML4E Framework
Mosquito data cleaner
Discrepancy Scaling for Unsupervised Anomaly Detection and Localization
Autonomously Adaptive Experimentation-Driven Pipeline
VALICY – a virtual validation system for AI/ML and complex software applications
SAGED: Error Detector for Tabular Data
Cost-effecient ML
ML Metrics Typology + AI Ethics Metrics
Calibrated confidence estimator
Inference scaling
Rare node co-activations in error detection
Data quality dashboard for Continuous Monitoring of Large Data Volumes
The IML4E Maturity Assessment Scheme
Privacy-friendly Image Preparation for TinyML
Model cards toolkit
CABC for MLOps
Resources
Resources
Conferences and Publications
Deliverables
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Up to date
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IML4E – Deliverables
IML4E
Resources
Deliverables
Baseline methods and techniques for data collection, processing, and valorisation
Download: PDF
| SQC
First Version of Methods and Techniques for Data Collection, Processing, and Valorisation
Download: PDF
| SQC
First Version of Tools for Data Collection, Processing, and Valorisation
Download: PDF
| SQC
Baseline methods and techniques for advanced model engineering
Download: PDF
First version of methods and techniques for advanced model engineering
Download: PDF
| SQC
First version of tools for advanced model engineering
Download: PDF
| SQC
Requirements for the IML4E Online Experimentation and Education Platform
Download: PDF
| SQC
Initial MLOps methodology and the architecture of the IML4E framework
Download: PDF
| SQC