1.1 training / development / test set - depth learning Lesson "Improving DNN" -Stanford Professor Andrew Ng - Code World

1.1 training / development / test set - depth learning Lesson "Improving DNN" -Stanford Professor Andrew Ng

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1.1 training / development / test set - depth learning Lesson "Improving DNN" -Stanford Professor Andrew Ng

1.2 deviation / variance - depth learning Lesson "Improving DNN" -Stanford Professor Andrew Ng

1.3 Machine Learning Basics - Lesson depth study "Improving DNN" -Stanford Professor Andrew Ng

1.7 Dropout- depth understanding of learning a second lesson "Improving DNN" -Stanford Professor Andrew Ng

1.5 Why regularization help prevent over-fitting - depth learning Lesson "Improving DNN" -Stanford Professor Andrew Ng

1.8 Other regularization method - deep learning Lesson "Improving DNN" -Stanford Professor Andrew Ng

1.6 The size of the development set and test set-Deep Learning Lesson 3 "Structured Machine Learning Project"-Professor Stanford Wu Enda

1.1 Ausbildung / Entwicklung / Test-Set - Tiefe Lernen Lektion "Verbesserung der DNN" -Stanford Professor Andrew Ng

1.5 Training / Development / Testing Partition-Deep Learning Lesson 3 "Structured Machine Learning Project" -Professor Stanford Wu Enda

3.3 Practical training of hyperparameters: Pandas vs. Caviar-Deep Learning Lesson 2 "Improving Deep Neural Networks"-Professor Stanford Wu Enda

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0.0 Table of Contents-The Third Lesson of Deep Learning "Structured Machine Learning Project"-Professor Stanford Wu Enda

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