Python-bloggers

Data Science Software Popularity Update

October 12, 2022 | Bob Muenchen

I have recently updated my extensive analysis of the popularity of data science software. This update covers perhaps the most important section, the one that measures popularity based on the number of job advertisements. I repeat it here as a blog post, so you don’t have to read the ...

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Hyper-Parameter Tuning with Python VIDEO

October 10, 2022 | Dr. Darrin

Hyper-parameter tuning is one way of taking your model development to the next level. This tool provides several ways to make small adjustments that can reap huge benefits. In the video below, we will look at tuning the hyper-parameters of a KNN model. Naturally, this tuning process can be used ...

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Refactoring Russian Doll Code

October 6, 2022 | The Jumping Rivers Blog

Refactoring Russian Doll Code Recently, I’ve been working with an environmental scientist to refactor a large R package. Let’s call her Jane. Jane inherited a mess of code, and had to ...

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R Shiny vs Shiny for Python: What are the Key Differences

October 6, 2022 | Dario Radečić

If you haven’t been living under a rock for the past couple of weeks, you’ve likely noticed some groundbreaking news in the Shiny department. Yes, it’s finally available for Python! But how is the current Shiny for Python version? How does R Shiny compare vs Shiny for ...

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Mocking Cognito in Python (at no cost)

October 6, 2022 | Mateusz Głowiński

Mocking up real services is a no-brainer, no one wants tests to affect the production environment in any way. Here's how to do that with AWS Cognito in Python. [...Read more...]

Containerizing Shiny for Python and Shinylive Applications

October 6, 2022 | Peter Solymos

Shiny for Python brings easy interactivity to web applications that build on the data and scientific stack of Python. Containerizing Py-Shiny apps is the next step towards deployment to a wide array of hosting options, including static hosting.

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Team Collaboration in R and Python Made Easy

October 6, 2022 | Python on RStudio

Bilingual teams that want to do serious data science require collaboration, transparency, and reproducibility across R and Python workflows while empowering professionals to work in their preferred language(s). Accomplishing this requires tools built for interoperability at scale and a shared standard between data science languages. Here are a few ... [...Read more...]

Prediction intervals (not only) for Boosted Configuration Networks in Python

October 5, 2022 | T. Moudiki

Prediction intervals for Machine Learning, using conformal prediction in Python package the-teller

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Cross-Validation with Python VIDEO

October 3, 2022 | Dr. Darrin

Cross-validation is a valuable tool for assessing a model’s ability to generalize. In the video below, we will look at how to use cross-validation with Python.

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Kernel SHAP in R and Python

September 30, 2022 | Michael Mayer

"R Python" continued... Kernel SHAP

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