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 :
- Create an ML model using open data
- Create a project on Giskard
- Upload the model & data in Giskard
- Model libraries :
- Deep learning : #pytorch #tensorflow
- Machine Learning : #scikit-learn #logistic_regression #random_forest #knn
- Text Based : #transformers #huggingface #bert #roberta
- How the prediction function is called :
- Pipeline : Models are created using #pipeline
- Wrapped Functions : Models use the traditional way of the whole process of data transformation and prediction using python #wrapped_function
- Data Types:
- #category_data
- #numeric_data
- #text_data
- Model Type :
- #classification
- #regression
| Notebook | Tags |
|---|---|
| Credit scoring classification model.ipynb | #scikit-learn #logistic_regression #random_forest #classification #category_data #numeric_data #pipeline |
| Email Classification Model.ipynb | #scikit-learn #nltk #transformers #huggingface #pytorch #bert #classification #text_data #category_data #numeric_data #pipeline #wrapped_function |
| House pricing regression model.ipynb | #scikit-learn #random_forest #catboost #regression #category_data #numeric_data #pipeline |
| Sentiment_Analysis_for_Twitter_Data_using_Roberta.ipynb | #transformers #huggingface #roberta #tweepy #datasets #classification #text_data #wrapped_function |
| Iris_demo.ipynb | #scikit-learn #knn #classification #numeric_data #category_data #wrapped_function #wrapped_function |
| Newspaper_classification.ipynb | #pytorch #torchtext #dataloader #classification #text_data #wrapped_function |
| Text_classification_Using_Tensorflow_Neural_Network.ipynb | #tensorflow #neural_network #classification #text_data #wrapped_function |