Python-bloggers

Elastic net regression has all the strengths of both ridge and lasso regression without the apparent weaknesses. As such this is a great algorithm for regularized regression. The video below explains how to use this algorithm with Python

High level Python & R functions for interacting with Techtonique forecasting API

If you truly want to wrap your head around a deep learning model, visualizing it might be a good idea. These networks typically have dozens of layers, and figuring out what’s going on from the summary alone won’t get you far. That’s why today we’ll show ...

It has been 6 months since the launch of Diffify, our website for comparing package releases. We are delighted to announce that, in addition to CRAN’s 20,000 R packages, you can now track 16...

There's more than one way to square a number in Python. Learn 4 approaches to Python squaring + some bonus tricks for lists.

Matplotlib is one of the longest standing and most comprehensive plotting libraries for Python. It is mostly used for creating static plots and its flexible customisation options make it a great c...

T-test: The most popular hypothesis test In today’s data-driven world, data is generated and consumed on a daily basis. All this data holds countless hidden ideas and information that can be exhausting to uncover. Data scientists commonly approach this problem using statistics to make educated guesses about data.  Any ...

Scaling Shiny apps requires load balancing with session affinity which is not a trivial matter. Read on to see how to do that on Heroku.

A Forecasting API, with examples

This post shows how filling histograms can be done in very different ways thereby connecting very different areas: from gradient boosted trees to SQL queries to one-hot encoding. Let's jump into it! Modern gradient boosted trees (GBT) like LightGBM, XGBoost and the HistGradientBoostingRegressor of scikit-learn all use two techniques on ...