At which point in the learning step can one achieve 100%?
Tuesday, 27 January 2026
by MJ De Sousa
In the context of machine learning, particularly within the framework provided by Google Cloud Machine Learning and its introductory concepts, the question of "At which point in the learning step can one achieve 100%?" brings forth important considerations regarding the nature of model training, validation, and the conceptual understanding of what 100% refers to in
Explain why the network achieves 100% accuracy on the test set, even though its overall accuracy during training was approximately 94%.
Saturday, 05 August 2023
by EITCA Academy
The achievement of 100% accuracy on the test set, despite an overall accuracy of approximately 94% during training, can be attributed to several factors. These factors include the nature of the test set, the complexity of the network, and the presence of overfitting. Firstly, the test set may differ in various aspects from the training
- Published in Artificial Intelligence, EITC/AI/TFF TensorFlow Fundamentals, TensorFlow in Google Colaboratory, Building a deep neural network with TensorFlow in Colab, Examination review
Tagged under:
Artificial Intelligence, Deep Learning, Neural Networks, Overfitting, Test Set, Training Accuracy