Machine learning will definitely be one of the key technologies of the 21st century. From self-driving cars to product suggestions on a website, machine learning is already part of our everyday life. So why not add machine learning capabilities to PostgreSQL? Cybertec has done just that.

We connect modern neural networks with solid, ready-to-use database technology. By combining various techniques, you can achieve top results with minimal effort. We open the door to next-generation applications.

pgneural is a collection of tools and functions for PostgreSQL that add machine-learning capabilities to PostgreSQL and allow you to run modern algorithms directly in your favourite database engine. pgneural also helps provide easier integration with libraries such as sklearn and TensorFlow.

Neural networks and machine learning can be used for a variety of purposes including, but not limited to:

  • Intelligent queries
  • Fraud detection
  • Process optimization
  • Timeline analysis (financial data, etc.)
  • Scientific models
  • Pattern detection
  • Data mining
  • Robotics
  • Game development

To make neural networks work efficiently, you need a professional database infrastructure that can store and handle large amounts of data quickly and efficiently.

Bring algorithms to the data

PostgreSQL pg neural

Taking advantage of neural networks

Neural networks simulate the way our brains work. In contrast to traditional technology, neural networks allow you to detect complex interactions between various factors. In other words, a neural network finds out by itself how things are connected and gives you a powerful tool to make use of this learning capability.

Neural networks are hand-tailored to fit your needs. To train a neural network, you need historic data. The system will then learn from these data and use this knowledge in the future to predict the output you need. This makes a neural network flexible and allows many different use cases.

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