To use the lecture examples and undertake the exercise in this repository, you should install the supplied environment.
Once you have downloaded the repository, navigate to the environment directory in your Ananconda prompt and type :
conda env create -f environment.yml
Once the environment has been installed, use :
conda activate complete_ml
to activate the environment, or select the environment as your kernel in VSCode.
Example notebooks can be opened here:
Auto ML:
Data Preprocessing and EDA:
Ensembles - Voting:
Feature Engineering:
Feature Selection:
Hyperparameter Optimisation:
Imbalanced Data:
K-fold validation:
Missing Data Imputation:
Model Calibration:
Pipelines: