Predictors and FeatureUnion in ML
Scikit-learn refers to machine learning algorithms as estimators. There are three different types of estimators: classifiers, regressors, and transformers. The inheritance of the second class determines what kind of estimator the model represents. We’ll divide the estimators into two groups based on their interface. These two groups are predictors and transformers, and in this blog, […]
Ensemble models and use of feature importance in tree-based models
Ensemble models Ensemble models are machine learning models that use more than one predictor to predict. A group of predictors forms an ensemble. In general, ensemble models perform better than using a single predictor. There are three ensemble models, bagging, boosting, and blending. Random forests The performance of a single decision tree will be limited, […]
How can we use BigQuery in preparing Data studio?
Before we dive into the use of BigQuery in preparing Google Data Studio, let’s take a moment to briefly have an idea about what is BigQuery, what is Google Data Studio and Google Data Studio BigQuery connector. What is Big Query? Big Query is an analytics data warehouse that lets users analyze large amounts […]
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