Dimensionality Reduction
Major Algorithms for Dimensionality Reduction are: Linear Methods: PCA (Principal Component Analysis) Eigen Decomposition SVD (Singular Value Decomposition) NMF (Non-Negative Matrix Factorization) ICA (Independent Component Analysis) LDA (Linear Discriminant Analysis)
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
Decision Tree Model for Classification
Decision Tree Models …
Class Imbalance Problem in Classification Domain
Class Imbalance Problem in Classification Domain …
Continue reading…Class Imbalance Problem in Classification Domain
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.
UnderFitting and OverFitting in ML
Understand the UnderFitting and OverFitting in ML. Here I am mentioning techniques to avoid them in case of linear models, non-linear models and Deep learning …
