[ DevCourseWeb.com ] Deep Learning with Python - Optimizing Deep Learning Models

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[ DevCourseWeb.com ] Deep Learning with Python - Optimizing Deep Learning Models

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文件大小：263.48M
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收录时间：2025-03-10
最近下载：2025-10-08

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文件列表

  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/05 - Using KerasTuner for hyperparameter tuning.mp4 24.6 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/07 - Training a deep learning model using callbacks.mp4 21.0 MB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/04 - Defining a tunable deep learning model in Keras.mp4 18.8 MB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/02 - Key hyperparameters in deep learning.mp4 15.6 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/06 - Learning rate scheduling.mp4 11.6 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/01 - Common loss functions in deep learning.mp4 11.1 MB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/03 - Methods for hyperparameter tuning.mp4 10.8 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/07 - Applying dropout regularization to a deep learning model.mp4 10.3 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/03 - Applying L1 regularization to a deep learning model.mp4 10.3 MB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/01 - Parameters versus hyperparameters.mp4 10.2 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/04 - Applying L2 regularization to a deep learning model.mp4 10.0 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/03 - Gradient clipping.mp4 9.9 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/04 - Applying gradient clipping to a deep learning model.mp4 9.4 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/05 - Adaptive Gradient Algorithm (AdaGrad).mp4 9.1 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/02 - Applying batch normalization to a deep learning model.mp4 8.4 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/02 - Lasso and ridge regularization.mp4 7.8 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/08 - Adaptive Moment Estimation (Adam).mp4 6.4 MB
  • ~Get Your Files Here !/07 - Conclusion/01 - Continuing to optimize deep learning models.mp4 6.4 MB
  • ~Get Your Files Here !/02 - 1. Optimizing Deep Learning Models/01 - The importance of optimizing deep learning models.mp4 6.3 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/01 - The bias-variance trade-off.mp4 6.1 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/02 - Batch gradient descent.mp4 5.9 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/04 - Mini-batch gradient descent.mp4 5.7 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/05 - Early stopping and checkpointing.mp4 5.3 MB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/01 - Batch normalization.mp4 5.2 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/06 - Dropout regularization.mp4 4.9 MB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/05 - Elastic Net regularization.mp4 4.9 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/03 - Stochastic gradient descent (SGD).mp4 4.8 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/06 - Root Mean Square Propagation (RMSProp).mp4 4.5 MB
  • ~Get Your Files Here !/01 - Introduction/01 - Optimizing deep learning models.mp4 3.7 MB
  • ~Get Your Files Here !/01 - Introduction/03 - Using the exercise files.mp4 2.9 MB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/07 - Adaptive Delta (AdaDelta).mp4 2.7 MB
  • ~Get Your Files Here !/01 - Introduction/02 - What you should know.mp4 1.2 MB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/02 - Key hyperparameters in deep learning.srt 12.9 kB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/05 - Using KerasTuner for hyperparameter tuning.srt 11.8 kB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/03 - Methods for hyperparameter tuning.srt 10.5 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/07 - Training a deep learning model using callbacks.srt 10.4 kB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/04 - Defining a tunable deep learning model in Keras.srt 10.0 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/06 - Learning rate scheduling.srt 8.4 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/01 - Common loss functions in deep learning.srt 8.1 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/03 - Gradient clipping.srt 8.0 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/05 - Adaptive Gradient Algorithm (AdaGrad).srt 7.8 kB
  • ~Get Your Files Here !/05 - 4. Hyperparameter Tuning Techniques/01 - Parameters versus hyperparameters.srt 7.6 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/02 - Lasso and ridge regularization.srt 6.6 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/04 - Mini-batch gradient descent.srt 6.3 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/02 - Batch gradient descent.srt 6.0 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/01 - The bias-variance trade-off.srt 5.8 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/05 - Early stopping and checkpointing.srt 5.8 kB
  • ~Get Your Files Here !/07 - Conclusion/01 - Continuing to optimize deep learning models.srt 5.6 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/08 - Adaptive Moment Estimation (Adam).srt 5.4 kB
  • ~Get Your Files Here !/02 - 1. Optimizing Deep Learning Models/01 - The importance of optimizing deep learning models.srt 5.2 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/04 - Applying L2 regularization to a deep learning model.srt 5.1 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/01 - Batch normalization.srt 5.0 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/03 - Stochastic gradient descent (SGD).srt 4.9 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/03 - Applying L1 regularization to a deep learning model.srt 4.7 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/06 - Dropout regularization.srt 4.6 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/02 - Applying batch normalization to a deep learning model.srt 4.5 kB
  • ~Get Your Files Here !/06 - 5. Advanced Training Techniques/04 - Applying gradient clipping to a deep learning model.srt 4.5 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/07 - Applying dropout regularization to a deep learning model.srt 4.5 kB
  • ~Get Your Files Here !/03 - 2. Regularization Techniques/05 - Elastic Net regularization.srt 4.1 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/06 - Root Mean Square Propagation (RMSProp).srt 3.9 kB
  • ~Get Your Files Here !/04 - 3. Loss Functions and Optimization Algorithms/07 - Adaptive Delta (AdaDelta).srt 2.9 kB
  • ~Get Your Files Here !/01 - Introduction/03 - Using the exercise files.srt 2.2 kB
  • ~Get Your Files Here !/01 - Introduction/01 - Optimizing deep learning models.srt 1.5 kB
  • ~Get Your Files Here !/01 - Introduction/02 - What you should know.srt 1.4 kB
  • Get Bonus Downloads Here.url 182 Bytes
  • ~Get Your Files Here !/Bonus Resources.txt 70 Bytes

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