The new integration is designed to give JFrog users a way to build, manage and deliver machine learning models and generative artificial intelligence-powered apps along with other software ...

Key features of the integration bring machine learning closer to the standard software development and production lifecycles, ensuring enhanced protection against deletion or modification of models.

Microsoft's SQL Server 2016 allows for R-based machine learning models to be stored in its databases and R code that uses the models to be hosted in its stored procedures and SQL scripts.

Machine learning has a wide range of applications in the finance, healthcare, marketing and transportation industries. It is used to analyze and process large amounts of data, make predictions ...

Similarly, the Scikit-Learn and TensorFlow libraries are employed for machine learning jobs, and Django is a well-liked Python web development framework. 5 Python libraries that help interpret ...

Automated machine learning pipelines: Kubernetes enables the automation of end-to-end machine learning pipelines, from data ingestion and pre-processing to model training and deployment. Tools like ...

More information: Yun-Fei Shi et al, Machine Learning for Chemistry: Basics and Applications, Engineering (2023). DOI: 10.1016/j.eng.2023.04.013 Provided by Engineering ...

With the newly announced integration of MindsDB with MariaDB, users can now create virtual AI tables in MariaDB which allow them to run automated machine learning models directly inside the database.