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Innovations and Objectives
Innovations and Objectives
Objectives
IML4E innovations
Case Studies
Case Studies
Basware
Granlund
Reaktor
Vitarex
Siemens
Results
Results
MLOps monitoring platform
MLOps Framework
Adversarial Test Toolbox
ML-Py-Stevedore
Data Quality Dashboard
ML Lineage
Mosquito data cleaner
MLOps Testing Methodology
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
Continuous data monitoring and cleaning dashboard for smart meters
MLOps Maturity Assessment Scheme
Privacy-friendly Image Preparation for TinyML
Model cards toolkit
Pipeline Probe
Data Quality Evaluation Tool
OSS MLOps platform
CABC for MLOps
Validation of pose estimation models
ML-Py-Stevedore
Resources
Resources
Conferences and Publications
Deliverables
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Up to date
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IML4E – Deliverables
IML4E
Resources
Deliverables
Training and Education Material
Download: PDF
| SQC
Final MLOps methodology and the IML4E framework
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| SQC
Baseline methods and techniques for data collection, processing, and valorisation
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| SQC
First Version of Methods and Techniques for Data Collection, Processing, and Valorisation
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| SQC
Second version of Methods and Techniques for Data Collection, Processing, and Valorisation
Download: PDF
| SQC
Baseline methods and techniques for advanced model engineering
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First version of methods and techniques for advanced model engineering
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| SQC
First version of tools for advanced model engineering
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| SQC
Second version of methods and techniques for advanced model eingineering
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| SQC
Second version of tools for advanced model eingineering
Download: PDF
| SQC
Requirements for the IML4E Online Experimentation and Education Platform
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| SQC
Initial MLOps methodology and the architecture of the IML4E framework
Download: PDF
| SQC