📚Use the TensorFlow Functional API to build sophisticated deep learning models.
💡Siamese neural networks enable one-shot image recognition.
🔎OpenCV provides image processing capabilities for real-time testing.
📈The model's architecture involves input images, hidden layers, and a distance layer.
💻Implement the model using TensorFlow and the Keras library for deep learning.
What is the TensorFlow Functional API?
—The TensorFlow Functional API allows for the creation of more complex and flexible deep learning models.
What are siamese neural networks?
—Siamese neural networks are used to determine the similarity between two images.
What is OpenCV?
—OpenCV is a library that provides image processing capabilities for real-time testing.
What components make up the model's architecture?
—The model's architecture includes input images, hidden layers, and a distance layer.
What libraries are used to implement the model?
—The model is implemented using TensorFlow and the Keras library for deep learning.
00:00Welcome to a video course on building a facial recognition app with deep learning.
01:00The course covers the entire process, from installing dependencies to integrating the model into an app.
06:00The TensorFlow Functional API is used to create sophisticated deep learning models.
08:00Siamese neural networks enable one-shot image recognition.
09:00OpenCV provides image processing capabilities for real-time testing.
10:00The model's architecture involves input images, hidden layers, and a distance layer.
11:00Implement the model using TensorFlow and the Keras library for deep learning.
12:00Learn how to build a facial recognition app with deep learning.
