scikit-learn
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scikit‑learn es la librería que democratizó el machine learning clásico en Python. Su API consistente, los más de 120 algoritmos incluidos y la integración con pandas convierten a scikit‑learn en el camino más rápido –y explicable– de los datos tabulares al valor de negocio.
Itrion opera 480 pipelines scikit‑learn en producción que calculan 58 M predicciones diarias, con una latencia P95 de 9 ms y cumplimiento ENS Alta & ISO 27017.
Precisión media en clasificación
Datos tabulares procesados
Tiempo medio de MVP
Ahorro cómputo CPU
Mapa rápido de algoritmos
| Familia | Algoritmo | Ventaja | Tiempo fit (1 M filas) |
|---|---|---|---|
| Clasificación | Logistic Regression | Base‑line interpretable | <4 s |
| RandomForest | Robusto outliers | 12 s | |
| HistGradientBoosting | Top performance CPU | 8 s | |
| Regresión | ElasticNet | Regularización mixta | <2 s |
| GradientBoosting | No lineal, explainable | 10 s | |
| Clustering | K‑Means++ | Segmentación simple | 6 s |
| Reducción Dim. | PCA (SVD) | Compresión lineal | 3 s |
Pipeline end‑to‑end con Itrion
1. Validación de esquema
Comprobación de tipos, rangos y valores nulos con pandera y Great Expectations.
2. Ingeniería de variables
Uso de ColumnTransformer para codificar categóricas, generar polinomios y escalar numéricas.
3. Búsqueda de hiperparámetros
OptunaCV con pruners asíncronos y 50 trials paralelos en 8 núcleos.
4. Exportación & ONNX
Conversión directa a onnx 1.15 → ONNX Runtime CPU/GPU.
5. Despliegue & Monitorización
FastAPI + uvicorn, métricas promQL y detección de drift Skops‑Monitor.
Fortalezas exclusivas de Itrion
Aceleración CPU con oneAPI
Integramos sklearnex y OpenVINO para acelerar SVM, k‑NN y árboles hasta 15× en Xeon Ice Lake.
Explainability legal
Generamos informes SHAP, LIME y Permutation Importance adaptados a IA Act UE (art. 13).
Low‑latency serving
Inferencia ONNX Runtime + AVX‑512 con latencia P95 ≤ 9 ms a 500 rps.
Governance MLOps
DVC para versionar datos, MLflow tracking y alertas de drift en Grafana.
Por qué elegir a Itrion
- • ROI inmediato: MVP operacional en ≤4 semanas con accuracy > benchmark sectorial.
- • Cost‑efficient: todo CPU – sin necesidad de GPU costosas.
- • Transparencia: informes explicables listos para auditores internos y externos.
- • Escalabilidad: integrado con SageMaker, Vertex AI y Databricks Serverless.
“Itrion logró clasificar préstamos con 0,94 ROC AUC y redujo el tiempo de scoring de 120 ms a 8 ms, cumpliendo directrices EBA.”
scikit-learn is the library that democratized classical machine learning in Python. Its consistent API, over 120 included algorithms, and integration with pandas make scikit-learn the fastest –and most explainable– path from tabular data to business value.
Itrion operates 480 scikit-learn pipelines in production calculating 58M daily predictions, with a P95 latency of 9 ms and compliance with ENS High & ISO 27017.
Quick map of algorithms
| Family | Algorithm | Advantage | Fit time (1M rows) |
|---|---|---|---|
| Classification | Logistic Regression | Interpretable base-line | <4 s |
| RandomForest | Robust to outliers | 12 s | |
| HistGradientBoosting | Top CPU performance | 8 s | |
| Regression | ElasticNet | Mixed regularization | <2 s |
| GradientBoosting | Non-linear, explainable | 10 s | |
| Clustering | K-Means++ | Simple segmentation | 6 s |
| Dim. reduction | PCA (SVD) | Linear compression | 3 s |
End-to-end pipeline with Itrion
1. Schema validation
Type, range and null checks with pandera and Great Expectations.
2. Feature engineering
Use ColumnTransformer to encode categoricals, generate polynomials, and scale numericals.
3. Hyperparameter search
OptunaCV with asynchronous pruners and 50 parallel trials on 8 cores.
4. Export & ONNX
Direct conversion to onnx 1.15 → ONNX Runtime CPU/GPU.
5. Deployment & Monitoring
FastAPI + uvicorn, promQL metrics and Skops-Monitor drift detection.
Exclusive strengths of Itrion
CPU acceleration with oneAPI
We integrate sklearnex and OpenVINO to accelerate SVM, k-NN and trees up to 15× on Xeon Ice Lake.
Legal explainability
We generate SHAP, LIME and Permutation Importance reports adapted to EU AI Act (art. 13).
Low-latency serving
ONNX Runtime inference + AVX-512 with P95 latency ≤ 9 ms at 500 rps.
Governance MLOps
DVC for data versioning, MLflow tracking and drift alerts in Grafana.
Why choose Itrion
- • Immediate ROI: Operational MVP in ≤4 weeks with accuracy > sector benchmark.
- • Cost-efficient: all CPU – no need for expensive GPUs.
- • Transparency: explainable reports ready for internal and external auditors.
- • Scalability: integrated with SageMaker, Vertex AI and Databricks Serverless.
“Itrion achieved loan classification with 0.94 ROC AUC and reduced scoring time from 120 ms to 8 ms, meeting EBA guidelines.”
scikit‑learn es la librería que democratizó el machine learning clásico en Python. Su API consistente, los más de 120 algoritmos incluidos y la integración con pandas convierten a scikit‑learn en el camino más rápido –y explicable– de los datos tabulares al valor de negocio.
Itrion opera 480 pipelines scikit‑learn en producción que calculan 58 M predicciones diarias, con una latencia P95 de 9 ms y cumplimiento ENS Alta & ISO 27017.
Precisión media en clasificación
Datos tabulares procesados
Tiempo medio de MVP
Ahorro cómputo CPU
Mapa rápido de algoritmos
| Familia | Algoritmo | Ventaja | Tiempo fit (1 M filas) |
|---|---|---|---|
| Clasificación | Logistic Regression | Base‑line interpretable | <4 s |
| RandomForest | Robusto outliers | 12 s | |
| HistGradientBoosting | Top performance CPU | 8 s | |
| Regresión | ElasticNet | Regularización mixta | <2 s |
| GradientBoosting | No lineal, explainable | 10 s | |
| Clustering | K‑Means++ | Segmentación simple | 6 s |
| Reducción Dim. | PCA (SVD) | Compresión lineal | 3 s |
Pipeline end‑to‑end con Itrion
1. Validación de esquema
Comprobación de tipos, rangos y valores nulos con pandera y Great Expectations.
2. Ingeniería de variables
Uso de ColumnTransformer para codificar categóricas, generar polinomios y escalar numéricas.
3. Búsqueda de hiperparámetros
OptunaCV con pruners asíncronos y 50 trials paralelos en 8 núcleos.
4. Exportación & ONNX
Conversión directa a onnx 1.15 → ONNX Runtime CPU/GPU.
5. Despliegue & Monitorización
FastAPI + uvicorn, métricas promQL y detección de drift Skops‑Monitor.
Fortalezas exclusivas de Itrion
Aceleración CPU con oneAPI
Integramos sklearnex y OpenVINO para acelerar SVM, k‑NN y árboles hasta 15× en Xeon Ice Lake.
Explainability legal
Generamos informes SHAP, LIME y Permutation Importance adaptados a IA Act UE (art. 13).
Low‑latency serving
Inferencia ONNX Runtime + AVX‑512 con latencia P95 ≤ 9 ms a 500 rps.
Governance MLOps
DVC para versionar datos, MLflow tracking y alertas de drift en Grafana.
Por qué elegir a Itrion
- • ROI inmediato: MVP operacional en ≤4 semanas con accuracy > benchmark sectorial.
- • Cost‑efficient: todo CPU – sin necesidad de GPU costosas.
- • Transparencia: informes explicables listos para auditores internos y externos.
- • Escalabilidad: integrado con SageMaker, Vertex AI y Databricks Serverless.
“Itrion logró clasificar préstamos con 0,94 ROC AUC y redujo el tiempo de scoring de 120 ms a 8 ms, cumpliendo directrices EBA.”
scikit-learn is the library that democratized classical machine learning in Python. Its consistent API, over 120 included algorithms, and integration with pandas make scikit-learn the fastest –and most explainable– path from tabular data to business value.
Itrion operates 480 scikit-learn pipelines in production calculating 58M daily predictions, with a P95 latency of 9 ms and compliance with ENS High & ISO 27017.
Quick map of algorithms
| Family | Algorithm | Advantage | Fit time (1M rows) |
|---|---|---|---|
| Classification | Logistic Regression | Interpretable base-line | <4 s |
| RandomForest | Robust to outliers | 12 s | |
| HistGradientBoosting | Top CPU performance | 8 s | |
| Regression | ElasticNet | Mixed regularization | <2 s |
| GradientBoosting | Non-linear, explainable | 10 s | |
| Clustering | K-Means++ | Simple segmentation | 6 s |
| Dim. reduction | PCA (SVD) | Linear compression | 3 s |
End-to-end pipeline with Itrion
1. Schema validation
Type, range and null checks with pandera and Great Expectations.
2. Feature engineering
Use ColumnTransformer to encode categoricals, generate polynomials, and scale numericals.
3. Hyperparameter search
OptunaCV with asynchronous pruners and 50 parallel trials on 8 cores.
4. Export & ONNX
Direct conversion to onnx 1.15 → ONNX Runtime CPU/GPU.
5. Deployment & Monitoring
FastAPI + uvicorn, promQL metrics and Skops-Monitor drift detection.
Exclusive strengths of Itrion
CPU acceleration with oneAPI
We integrate sklearnex and OpenVINO to accelerate SVM, k-NN and trees up to 15× on Xeon Ice Lake.
Legal explainability
We generate SHAP, LIME and Permutation Importance reports adapted to EU AI Act (art. 13).
Low-latency serving
ONNX Runtime inference + AVX-512 with P95 latency ≤ 9 ms at 500 rps.
Governance MLOps
DVC for data versioning, MLflow tracking and drift alerts in Grafana.
Why choose Itrion
- • Immediate ROI: Operational MVP in ≤4 weeks with accuracy > sector benchmark.
- • Cost-efficient: all CPU – no need for expensive GPUs.
- • Transparency: explainable reports ready for internal and external auditors.
- • Scalability: integrated with SageMaker, Vertex AI and Databricks Serverless.
“Itrion achieved loan classification with 0.94 ROC AUC and reduced scoring time from 120 ms to 8 ms, meeting EBA guidelines.”
At Itrion, we provide direct, professional communication aligned with the objectives of each organisation. We diligently address all requests for information, evaluation, or collaboration that we receive, analysing each case with the seriousness it deserves.
If you wish to present us with a project, evaluate a potential solution, or simply gain a qualified insight into a technological or business challenge, we will be delighted to assist you. Your enquiry will be handled with the utmost care by our team.
At Itrion, we provide direct, professional communication aligned with the objectives of each organisation. We diligently address all requests for information, evaluation, or collaboration that we receive, analysing each case with the seriousness it deserves.
If you wish to present us with a project, evaluate a potential solution, or simply gain a qualified insight into a technological or business challenge, we will be delighted to assist you. Your enquiry will be handled with the utmost care by our team.