[Helsinki] Pond on Island

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[Helsinki] Squirrel

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Visualizing Likert Scale Survey Data

I’m currently helping to evaluating a large market research survey, which ueses Likert Scales. To visualize the data I’ve tried several plots. The plots below where created with artificially created data to expose the strengths and weaknesses of different plot types. Data distribution: You can find the code for all plots here! Bar Plot: Mean Values Pros: Easy to create Simple to read Q3 – Q5 distinguishable Cons: Hides a lot complexity Doesn’t show spread Creates high confidence in shown values Bar Plot: Mean values and Standard Deviation Extension of first plot.
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Morphing Pizza

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F1-Score rises while Loss keeps increasing

I’ve recently run into a paradoxical situation while training a network to distinguish between to classes. I’ve used cross entropy as my loss of choice. On my training set the loss steadily decreased while the F1-Score improved. On the validation set the loss decreased shortly before increasing and leveling off around ~2, normally a clear sign for overfitting. However the F1-Score on the validation set kept rising and reached ~0.92, with similarly high presicion and recall.
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Human Machine Co-Creation

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Weizen Kastenbrot mit Saaten

Ein einfaches Rezept für ein Kastenbrot aus Weizenmehl. Die Zusammensetzung der Saaten kann beliebig angepasst werden. Vorteig: 250g Weizenmehl 550 250g Wasser 60g Anstellgut (TA200) Saaten: 80g Sonnenblumkerne 40g Leinensamen 40g Haferflocken 160g heißes Wasser (ca. 90° C) Hauptteig Vorteig Saaten 200g Weizenmehl 550 15g Salz 5g Hefe Zutaten des Vorteigs gut vermengen und 12 Stunden bei Raumtemperatur gehen lassen Saaten mischen und mit heißem Wasser übergießen. Mit eine Klarsichtfolie abdecken und ca.
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Archive: Master Thesis Notes

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Blog Running On New Server

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Django FormView Lifecycle

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