課程大綱： Advanced Deep Learning with Keras and Python培訓
Introduction
Keras and Deep Learning Frameworks
TensorFlow and Theano back-ends
Keras vs Tensorflow
Data and Machine Learning
Tabular data, visual data, unstructured data, etc.
Unsupervised learning, supervised learning, reinforcement learning, etc.
Preparing the Development Environment
Installing and configuring Anaconda
Installing Keras with a TensorFlow back-end
Neural Networks in Keras
Using Keras functional API to build a network
Pre-processing and fitting data
Defining a Keras model
Mutiple Input and Output Networks
Building two input-networks
Representing high-cardinality data
Merging layers
Extending the two input-network
Building neural networks with multiple outputs
Solving multiple problems simultaneously
Training and Pre-Training
Training models
Saving and loading models
Using ResNet50 on models
TensorBoard
Exporting Keras logs
Visualizing a computational graph and training progress
Google Cloud
Exporting models
Uploading Keras models
Using a model in Google Cloud
Summary and Conclusion
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