Welcome to the TensorFlow 2 시작하기 course! This comprehensive program covers building, training, evaluating, and predicting with sequential models using TensorFlow 2. You will also learn about model validation, normalization, implementing callbacks, and model saving and loading. The course culminates in a Capstone project integrating the learned concepts. Perfect for both beginners and experienced TensorFlow 1.x users.
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This TensorFlow 2 course covers an introduction to TensorFlow, sequential model API, validation, normalization, callbacks, and model saving and loading, culminating in a Capstone project.
This module introduces TensorFlow and its new features, including an overview of the course and setting up TensorFlow 2.
Module 2 welcomes you to the sequential model API, covering topics such as building sequential models, convolution and pooling layers, compiling models, and customizing methods.
Module 3 focuses on validation, normalization, and callbacks, including the introduction of validation sets, model normalization, callbacks, and early stopping and patience.
Module 4 delves into model saving and loading, covering topics such as saving and loading model weights, saving criteria, saving entire models, loading pre-trained Keras models, and TensorFlow Hub modules.
The Capstone project module welcomes you to the final project, culminating in a comprehensive Capstone project to integrate the learned concepts.
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