Getting Started With Apache® Spark™ on Databricks

Machine Learning Overview To access all the code examples in this stage, please import the Population vs. Price Linear Regression notebook. As organizations create more diverse and more user-focused data products and services, there is a growing need for machine learning, which can be used to develop personalizations, recommendations, and predictive insights. Apache Spark’s Machine Learning Library (MLlib) allows data scientists to focus on their data problems and models instead of solving the complexities surrounding distributed data (such as infrastructure, configurations, and so on). Accessing the sample data The easiest way to work with DataFrames is to access an example dataset. We have made a number of datasets available in the /databricks-datasets folder which is accessible from Databricks. For example, to access the file that compares city population vs. median…


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