DEEP LEARNING MODELS PRACTICE
NEW_TEMPLATE_IMP_DL_MODELS.ipynb
TEMPLATE_MODEL_TRAINING.ipynb
Encrypted_deep_learning_final_toy_dataset_training.ipynb
Final_encrypted_dl_project_MNIST.ipynb
Final_federated_learning_project.ipynb
Final_secured_fed_securing.ipynb
PATE_ANALYSIS_AND_IMPLEMENTATION.ipynb
Section 1 - Differential Privacy.ipynb
Section 2 - Federated Learning.ipynb
Section 3 - Securing Federated Learning.ipynb
Section 4 - Encrypted Deep Learning.ipynb
Section 4b - Encrypted Keras Client.ipynb
adding_laplacian_noise_global_diff_privacy.ipynb
annotating_unlabelled_dataset_using_dp_query.ipynb
differential_privacy_attack.ipynb
differential_privacy_private_dbs.ipynb
differential_privacy_sensitvity1.ipynb
encrypted_deep_learning_addition_subtraction_scalar_multiplication.ipynb
encrypted_deep_learning_in_pysyft.ipynb
federated_learning_advanced_remote_tensoroperations.ipynb
federated_learning_learning_a_simple_model.ipynb
federated_learning_project_remote_arithmetic.ipynb
noise_and_without_noise_db_analysis.ipynb
random_noise_analysis_differential_private_ai.ipynb
secured_federated_learning.ipynb
udacity-logo-vert-white.png
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