摘要： Bayesian Target Encoding is a feature engineering technique used to map categorical variables into numeric variables. The Bayesian framework requires only minimal updates as new data is acquired and is thus well-suited for online learning. Furthermore, the Bayesian approach makes choosing and interpreting hyperparameters intuitive. I developed this technique in the recent Avito Kaggle Competition, where my team and I took 14th place out of 1,917 teams. We found that the Bayesian target encoding outperforms the built-in categorical encoding provided by the LightGBM package.
摘要： It is important to actually work on different kinds of data and projects along with learning the data science concepts. Some datasets are very popular and a lot more are easily available on the web
摘要： DataStax Apache Cassandra as a Service, a Database as a Service offering, and DataStax Insights, a performance management service, to be first of platform’s offerings built to simplify application development