MLA 003 Storage: HDF, Pickle, Postgres

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Explains the fundamental differences between tensor dimensions, size, and shape, clarifying frequent misconceptions—such as the distinction between the number of features ("columns") and true data dimensions—while also demystifying reshaping operations like expand_dims, ...

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O'Reilly's 2017 Data Science Salary Survey finds that location is the most significant salary determinant for data professionals, with median salaries ranging from $134,000 in California to under $30,000 in Eastern Europe, and highlights that negotiation skills can lead ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

When you build a machine learning model, the first step is always to load your data. Typically this means downloading files from object storage, or querying a database. To speed up the process, why not build the model in ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. S3 ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

The most expensive part of working with massive data sets is the work of retrieving and processing the files that contain the raw information. FeatureBase (formerly Pilosa) avoids that overhead by converting the data int ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Sometimes, however, one of those transformation ...