This week’s blog is about attention to detail. When I was a Training Instructor in the Air Force, I instilled attention to detail by enforcing uniform standards. I had to make sure the buttons were buttoned, the belt was the correct length, boots were shined and correctly tied. I found myself this week thinking about attention to detail and using the Andaconda environment.
I learned about how pictures were processed during the malaria tutorial. In Andaconda you must first load up Spyder as a python IDE, then upload Tensorflow and Keras before I could start importing pictures. These are steps that were not in the tutorial. Many errors were to unfamiliarity with the environment setup. Only until I set up the environment I was able to set up the malaria tutorial.
The programming was pretty easy since I just cut and paste while trying to understand simultaneously. I was amazed that most of the work is done by the packages. Decisions must be made on the complexity of the data. For example do I use greyscale as a 2D array or do I use a 3D array for the blue, green, red layers. It was an experience that I am still trying to unfold in my mind to truly understand the data pipeline.
During a lecture on diabetes by Souptik Barua, I found it to hit me on a personal level. I am prediabetic. The statistics were dead on in my case. The use of the M^3 cycle had me thinking. The first M is measure. I measured my glucose level by pricking my finger everyday for a month. I then measured my food intake and then logged in my exercise. The next step is model where we analyze the data and predict the outcome. The last part was modify or use behavioral science to tear down the barriers and incorporate technology to make better choices.
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