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Deep learning is a subfield of machine learning that focuses on neural networks with multiple layers, also known as deep neural networks. Deep learning with TensorFlow and Keras in Python involves building and training neural networks for a variety of tasks, such as image classification, natural language processing, and more.
This deep dive will cover the fundamental concepts, tools, and techniques for working with deep learning using TensorFlow and Keras.
I. Introduction to Deep Learning:
1. Neural Networks Basics:
- A neural network is composed of layers of interconnected nodes or neurons.
- Each layer may have weights, biases, and activation functions.
2. Feedforward Neural Networks:
- Information flows from input to output without cycles.
- Commonly used for tasks like image classification.
II. TensorFlow and Keras:
1. TensorFlow:
- An open-source machine learning framework developed by the Google Brain team.
- Provides a comprehensive set of tools for building and deploying machine learning models.
