Instructions to use Nabeeha-Shafiq/MLFinalProject with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Nabeeha-Shafiq/MLFinalProject with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Nabeeha-Shafiq/MLFinalProject") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- dropout_nn_model
- logistic_regression_en_model
- logistic_regression_l1_model
- logistic_regression_l2_model
- random_forest_max_depth_10_min_samples_5
- random_forest_max_depth_15_min_samples_2
- random_forest_max_depth_5_min_samples_10
- regularised_nn_model
- simple_nn_model
- svm_rbf_C_0.1
- svm_rbf_C_1
- svm_rbf_C_10
- 1.75 kB