I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

Next, the demo trains a logistic regression model using raw Python, rather than by using a machine learning code library such as Microsoft ML.NET or scikit. [Click on image for larger view.] Figure 1: ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Patrick Royston, Douglas G. Altman, Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling, Journal of the Royal Statistical Society. Series C (Applied ...

The proportional hazards model is frequently used to evaluate the effect of treatment on failure time events in randomised clinical trials. Concomitant variables are usually available and may be ...

The #Electricity4All Python Challenge: an opportunity to engage the public in improving modelling solutions for sustainable development policies 28 July 2016 During the HLPF 2016, the Development ...

else: actuals.insert(i,1) Python has many terse one-line syntax shortcuts because the language was designed to be used interactively. Training the Logistic Regression Model Training the model begins ...