Installing a Blueqat quantum computing SDK on amazon sagemaker for a new machine learning environment

Amazon sagemaker is a platform to learn machine learning with data. Recently quantum computing is started to use in the field of a new quantum machine learning. Usually we use python on machine…

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Practicing Data Visualization with the North American Breeding Bird Survey

Data visualization is everywhere. Beautiful and coherent charts, graphs and fancy little graphics transform raw numbers into entire stories.

When it comes to data visualization, I could be more clueless, but I’m not exactly a master either. My go-to technique is to bludgeon data into submitting to my will, which usually requires a great deal of trial or error and compensating for my lack of skills with dogged manual labor as necessary.

This project proved no different. With an impressive “looking for data” to “actually manipulating data” ratio of 15:1, I bludgeoned, trialed, mostly erred and compensated my way through a faulty dataset and a couple of different data visualization platforms to arrive here and with — even more impressively, I think — something to show.

Customizing a data set using the online retrieval tool.

In order to facilitate learning and experimentation, I decided to select just eleven common birds from the data set on which to practice.

The following charts show the population trends of two birds between 1968 and 2014 at Fish Rock, CA for two birds: the Brown Creeper and Brandt’s Cormorant. Created with Excel.

The purpose of my project being to research, learn, and apply aesthetic techniques for presenting data relating to environmental topics, I established a couple of different goals:

1. Research and learn techniques of data visualization.

2. Apply methods of data visualization to a specific topic.

3. Produce a collection of infographics.

4. Accumulate new skills relevant to future projects.

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