The Deep Learning with Keras Workshop
Matthew Moocarme Mahla Abdolahnejad Ritesh Bhagwat更新时间：2021-06-18 18:13:53
最新章节：9. Sequential Modeling with Recurrent Neural Networks封面
版权信息
Preface
1. Introduction to Machine Learning with Keras
Introduction
Data Representation
Data Preprocessing
Life Cycle of Model Creation
scikit-learn
Keras
Model Training
Model Tuning
Summary
2. Machine Learning versus Deep Learning
Introduction
Linear Transformations
Introduction to Keras
Summary
3. Deep Learning with Keras
Introduction
Building Your First Neural Network
Model Evaluation
Summary
4. Evaluating Your Model with Cross-Validation Using Keras Wrappers
Introduction
Cross-Validation
Cross-Validation for Deep Learning Models
Model Selection with Cross-Validation
Summary
5. Improving Model Accuracy
Introduction
Regularization
L1 and L2 Regularization
Dropout Regularization
Other Regularization Methods
Hyperparameter Tuning with scikit-learn
Summary
6. Model Evaluation
Introduction
Accuracy
Imbalanced Datasets
Confusion Matrix
Summary
7. Computer Vision with Convolutional Neural Networks
Introduction
Computer Vision
Convolutional Neural Networks
The Architecture of a CNN
Image Augmentation
Summary
8. Transfer Learning and Pre-Trained Models
Introduction
Pre-Trained Sets and Transfer Learning
Fine-Tuning a Pre-Trained Network
Summary
9. Sequential Modeling with Recurrent Neural Networks
Introduction
Sequential Memory and Sequential Modeling
Recurrent Neural Networks (RNNs)
Long Short-Term Memory (LSTM)
Summary
Appendix
1. Introduction to Machine Learning with Keras
2. Machine Learning versus Deep Learning
3. Deep Learning with Keras
4. Evaluating Your Model with Cross-Validation Using Keras Wrappers
5. Improving Model Accuracy
6. Model Evaluation
7. Computer Vision with Convolutional Neural Networks
8. Transfer Learning and Pre-Trained Models
9. Sequential Modeling with Recurrent Neural Networks
更新时间：2021-06-18 18:13:53