We have built this repository to help you in the process of integrating Giskard by providing multiple notebooks. This repository has various notebooks which will help you to:

1. Create an ML model using open data
2. Create a project on Giskard
3. Upload the model & data in Giskard

1. Model libraries:
   1. #pytorch #tensorflow #scikit-learn #logistic_regression #random_forest #knn #transformers #huggingface #bert #roberta
2. How the prediction function is called:
   1. #pipeline: Models are created using
   2. #wrapped_function: Models use the traditional way of the whole process of data transformation and prediction using python
3. Data Types:
   1. #category_data
   2. #numeric_data
   3. #text_data
4. Model Type:
   1. #classification
   2. #regression