Which programming languages are primarily supported in Databricks for machine learning tasks?

Databricks primarily supports Python, R, Scala, and SQL for machine learning tasks, making this choice the most relevant for modern data science and machine learning applications.

Python is the most popular language in the data science community, known for its ease of use and the vast ecosystem of libraries such as TensorFlow, PyTorch, and Scikit-learn, which facilitate machine learning development. R is another widely used language, especially favored in statistical analysis and data visualization, and has robust ML libraries as well. Scala enables users to work with Apache Spark, a core component of Databricks, allowing for efficient large-scale data processing and machine learning. SQL is essential for data manipulation and querying within databases, making it integral for preparing and exploring data in machine learning workflows.

Other options provided, like Java and C++, are not primarily focused on machine learning within the context of Databricks, as they lack the comprehensive libraries and community support that Python, R, Scala, and SQL provide. HTML, CSS, and JavaScript are web development languages, not designed for machine learning tasks. PASCAL and FORTRAN are outdated languages that are rarely used in the field of modern machine learning. Thus, the combination of Python, R, Scala, and