Ciencia de datos

La ciencia de datos permite a las organizaciones extraer información útil de los datos mediante análisis estadísticos, aprendizaje automático y modelado predictivo. Exploramos herramientas, técnicas, aplicaciones prácticas y mejores prácticas para respaldar la toma de decisiones basada en datos y los esfuerzos de transformación digital.

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MLOps

Aprendizaje Federado: 7 Casos de Uso y Ejemplos

Ciencia de datosJun 11

According to recent McKinsey analyses, the most pressing risks of AI adoption include model hallucinations, data provenance and authenticity, regulatory non-compliance, and AI supply chain vulnerabilities. Federated learning (FL) has emerged as a foundational technique for organizations seeking to mitigate these risks.

Ciencia de datosJun 10

57 Conjuntos de datos para modelos de ML e IA

Data is required to leverage or build generative AI or conversational AI solutions. You can use existing datasets available on the market or hire a data collection service. We identified 57 datasets to train and evaluate machine learning and AI models.

Ciencia de datosMay 11

Calidad de los datos de IA: Desafíos y mejores prácticas

Poor data quality delays the successful deployment of AI and ML projects. Even the most advanced AI algorithms can yield flawed results if the underlying data is of low quality.

Ciencia de datosAbr 24

Prueba de referencia de base de datos de grafos: Neo4j vs FalkorDB vs Memgraph

We benchmarked Neo4j, FalkorDB, and Memgraph on a synthetic graph derived from 120,000 Amazon product reviews (381K nodes, 804K edges).

Ciencia de datosEne 27

Principales Plataformas de ML sin Código: Alternativas a ChatGPT

We benchmarked 4 no-code machine learning platforms across key metrics: data processing (handling missing values, outliers), model setup and ease of use, accuracy metrics output, availability of visualizations, and any major limitations or notes observed during testing. No-code machine learning tools benchmark Note: Scores represent average performance across kNN and Logistic Regression where applicable.