Time Series : Analysis and Forecasting
Time Series Data is the one that have Date Time as key feature to it. Along with that we can have another variable that is to be predicted (i.e. Target
UnSupervised Machine Learning
Here we only have Features but don’t have any Target column in our dataset, hence its known as UnSupervised ML. It’s more complex as compared to Supervised ML, and also
Ensemble Models
Types of Ensemble Models: Bagging Models Random Forest ExtraTree Classifier/Regressor Boosting Models AdaBoost (Adaptive Boosting) GBM (Gradient Boosting Machine) XGBoost (Xtreme Gradient Boosting) LightGBM CatBoost Stacking Models BAGGING MODELS All
Statistics for Every Data Scientist
Statistics is the foundation for every Data Scientist. Without good Stats knowledge, its difficult to comprehend the internal working and inferencing power of any Machine Learning model. Statistics is the art of
Class Imbalance Problem in Classification Domain
Class Imbalance Problem in Classification Domain …
Continue reading…Class Imbalance Problem in Classification Domain
Non-Linear Models for Regression
So far we discussed about the linear models of Regression like Linear Regression [OLS] and SVM [with kernel as linear]. Here we will talk about the non-linear regression models like
Ridge and Lasso Regression
When Linear Models like Linear Regression (OLS) model starts to show signs of Overfit, we have to consider Generalization. One of the way to achieve the same is via Regularization.