Data science is often a case of brining the tools to the problems and data, instead of insisting on bringing the problems and data to the tools.

To support cross-language data science we have been working on cross-language tools, documentation, and training.

For example:

vtreat data preparation package for supervised machine learning available both for vtreat R users and for vtreat Python users. Video lectures: advanced data preparation for R users video, and advanced data preparation for Python users video.

We have task-oriented cross-linked documentation:

• Regression: R regression example, fit/prepare
  interface,
  R regression example, design/prepare/experiment
  interface,
  Python regression
  example.
• Classification: R classification example, fit/prepare
  interface,
  R classification example, design/prepare/experiment
  interface,
  Python classification
  example.
• Unsupervised tasks: R unsupervised example, fit/prepare
  interface,
  R unsupervised example, design/prepare/experiment
  interface,
  Python unsupervised
  example.
• Multinomial classification: R multinomial classification
  example, fit/prepare
  interface,
  R multinomial classification example, design/prepare/experiment
  interface,
  Python multinomial classification
  example.

Categories: Administrativia Opinion Tutorials

Tagged as: pydata R vtreat

jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.