Data Preparation

August 1, 2019

Automated Execution of Multiple KNIME Workflows

When using the open source KNIME Analytics Platform to build sophisticated data processing and analysis pipelines, I often find myself building workflows that consist of so many nodes they become difficult to manage.  This complexity can be managed by grouping nodes into processing stages and then bundling those stages into meta-nodes so that the overall workflow layout is easier to follow. However, I’ve found that this approach still leaves workflows unwieldy to work with as you still have to open the meta-nodes to explore and troubleshoot their processing.  Over the years I’ve worked with KNIME, I’ve developed a habit of […]
April 12, 2019

Data Preparation for Machine Learning: Vector Spaces

Machine learning algorithms often rely on certain assumptions about the data being mined. Ensuring data meet these assumptions can be a significant portion of the preparation work before model training and predicting begins. When I began my data science journey, I was blissfully unaware of this and thought my preparation was done just because I had stuffed everything into a table. Feeding these naïvely compiled tables into learners I wondered why some algorithms never seemed to perform well for me. As I began digging into the algorithms themselves, many referred to vector space operations as being fundamental to their function. […]
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