QUANT AI Lab

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Resumen

We use a combination of artificial intelligence, operational research and quantum mechanics as an accelerator to meet our challenges: Data Mining & Data Governance: Identification, extraction, structuring, processing, analysis, and visualization of data, covering the entire life cycle, from its origin to its final actuation. Predictive Analytics: Development of solutions for decision-making and recommendation, early warning systems, anomaly detection and predictive models to anticipate behaviors, always using the most appropriate approach to each case (deep neural networks or deep learning, decision trees , Bayesian networks, clustering, etc). Natural Language Processing (NLP): Natural language processing making possible the extraction of structured and actionable knowledge from one of the information sources with the greatest potential, such as human language. For this, capacities such as transcription and analysis of conversations, speech synthesis, text classification, discovery of latent categories, etc. are contemplated. Computer Vision: Advanced image processing and analysis including object classification, detection, and segmentation systems, facial analysis, optical character recognition and extraction in documents, etc. Operational Research: Development of advanced analytical models that combine statistical analysis, mathematical modeling, and optimization techniques to assist in decision-making in complex problems. Quantum Mechanics: Vanguard in the application of quantum computing, one of the engines of the next technological revolution and with a direct impact on fields such as artificial intelligence, security, financial analysis, etc.

Sitio web
http://www.quant.global
Teléfono
El número de teléfono es +34 646 440 718
Sector
Servicios y tecnologías de la información
Tamaño de la empresa
11-50 empleados
Sede
Paris, Île-de-France
Tipo
De financiación privada
Fundación
2019
Especialidades
Artificial Intelligence, Quantum Computing, Big Data, Machine Learning, NLP y Computer Vision

Por favor, para apuntarte a este trabajo visita www.quant.global.