AI Intelligence Center
Continuous Model Self-Training & Ingestion Console
Model Version
v4.1.24
Updates live after user uploads
Resumes In Dataset
482
Total training samples
Validation Accuracy
99.98%Infinity Level
Target benchmark: 99.99%
Validation Loss
0.0001
Log-loss rate value
Prepare & Train Model Continuously
Each time a user uploads their resume to analyze, our core AI engine parses skills, mappings, and credentials. It automatically feeds this metadata back into the dataset to train itself and optimize mapping algorithms once for every uploaded file.
Model Performance History
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Ingested Skills Taxonomy
Normalized canonical terms automatically extracted and cataloged from uploaded user CVs:
React NativeKubernetesWebAssemblyTypeScriptRustNode.jsGoPythonAWSDockerGraphQLApollo ServerPyTorchTensorFlowREST APIsPostgreSQLRedisNext.js
Dynamic skills matching categoryActive
Training Ingestion History
| Epoch | Trigger Source Resume | Dataset Size | Validation Loss | Validation Accuracy | Newly Ingested Skills | Timestamp |
|---|