Part I Building Models 1. Introduction to TensorFlow What Is Machine Learning? Limitations of Traditional Programming From Programming to Learning What Is TensorFlow? Using TensorFlow Installing TensorFlow in Python Using TensorFlow in PyCharm Using TensorFlow in Google Colab Getting Started with Machine Learning Seeing What the Network Learned Summary 2. Introduction to Computer Vision Recognizing Clothing Items The Data: Fashion MNIST Neurons for Vision Designing the Neural Network The Complete Code Training the Neural Network Exploring the Model Output Training for Longer-Discovering Overfitting Stopping Training Summary 3. Going Beyond the Basics: Detecting Features in Images Convolutions Pooling Implementing Convolutional Neural Networks Exploring the Convolutional Network Building a CNN to Distinguish Between Horses and Humans The Horses or Humans Dataset The Keras Image Data Generator CNN Architecture for Horses or Humans Adding Validation to the Horses or Humans Dataset Testing Horse or Human Images Image Augmentation Transfer Learning Multiclass Classification Dropout Regularization Summary ……
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