Understanding which model performs better with respect to your dataset and objective is a critical step in machine learning. Moreover, it is crucial to know how to make your particular model perform better than usual.
In this challenge, we will explore the concepts of overfitting, underfitting and cross validation over a variety of models we have studied so far via visualization and understand how to improve a model's performance using techniques like regularization and basic hyperparameter tuning.
# Open a new notebook in colab and run the below command to
# import the entire repository for proper functioning of the notebooks
!git clone https://github.com/DeepConnectAI/challenge-week-6.gitHow to get the data using wget?
# Bike Dataset for Task 1
!wget https://github.com/DeepConnectAI/challenge-week-6/raw/master/data/bike.csv
# Employee Attrition Dataset for Task 2
!wget https://github.com/DeepConnectAI/challenge-week-6/raw/master/data/attrition.csvThis is not a huge repository therefore can easily be downloaded.
# Clone the repository
$ git clone https://github.com/DeepConnectAI/challenge-week-6.git
# Go to project directory
$ cd challenge-week-6
# Open up the jupyter notebook if installed
$ jupyter notebook