Tasks performed:
- Learned about high-dimesional datasets.
- Feature Selection:Learned how to visualize a dataset and drop the unnecessary features that hold little information either duplicates of other features or donot show any variance.
- Selection of Model accuracy: How to build a model from the most important feature for predicting a particular target feature.
- Feature extraction: Learned about dimesionality reduction algorithm, Principal Component Analysis(PCA)
