flask scikit-learn

Example Project Template: Serve a Scikit-learn Model via a Flask API

27 Jun 2018   Full (albeit simple) example on how to create a simple Flask API to serve predictions using a pre-trained scikit-learn model. Includes supporting features such as logging, error handling, input validation, etc. Full code available on Github.

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permissions linux

Default Permissions for Users, Directories and Files on Linux: Examples

23 Jun 2018   Set default permissions for all files/directories created by a user on Linux using umask. Additionally, use Access Control Lists (ACLs) for all files and directories created under a given directory too.

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matplotlib labels annotation

Add Labels and Text to Matplotlib Plots: Annotation Examples

23 Jun 2018   Examples on how to add simple annotations and labels to your matplotlib plots.

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How to Structure Software Projects: Python Example

22 Jun 2018   Here are a couple of templates to structure software projects. You need to think about structure because it is the single largest threat to your codebase as your project grows from small to medium-largish size. If you neglect to maintain project structure you risk having your project suffer death by entropy.

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Crypto Asset Overview: Ravencoin

16 Jun 2018   Short overview with the least you need to know about Ravencoin and the RVN token.

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Pandas Dataframe: Union and Concat Examples

14 Jun 2018   Emulate SQL union and union all behaviour, among other stuff.

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Pandas Dataframe: Replace Examples

14 Jun 2018   Call the replace method on Pandas dataframes to quickly replace values in the whole dataframe, in a single column, etc.

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Crypto Asset Overview: 0x Project and the ZRX Token

05 Jun 2018   Short overview with the least you need to know about the 0x protocol

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Latex Image Examples: Sizing, Positioning, Captioning, etc

03 Jun 2018   Examples on how to work with images on LaTeX and platforms that support it, such as ShareLaTeX and Overleaf.

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machine-learning metrics

Evaluation Metrics for Regression Problems: Quick examples + Reference

26 May 2018   Regression problems are evaluated against specific metrics that analyze whether the residuals (difference between actual and predicted values) indicate that a fitted model is a good fit for the data. Here are some of the most commonly-used metrics in that domain.

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