PostgreSQL database system: Use machine learning functions via Python Analysis environment costs money and time Use Python’s ML functions in PostgreSQL Prepare data for modeling Convert alphanumeric values ​​into numbers More values ​​against a wrong order Train models with partial data Conclusion Article in iX 11 / 2020 read Modern applications are increasingly integrating machine learning V experienced (ML) to facilitate decision-making and automate manual processes. For example, visitors to websites receive individual suggestions for purchasing behavior or Alexa, Siri and Co. act as virtual assistants.

Many of these methods are based on statistical models that describe situations and relationships or make predictions for future situations. They are often used when analyzing large amounts of data (big data). In this environment, analysis frameworks have emerged in recent years that make it possible to integrate various data sources and analyze them with ML functions. A prominent representative of these applications is Apache Spark.

Analysis environment costs money and Time If the data is not in data warehouses or analytical databases, required Their provision enables the transfer to a separate analysis environment in which modeling and calculation take place. This process is called “Extract -Transform – Load” (ETL).

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