Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow. It is designed to enable fast experimentation with deep learning models.
Key Features
- User-Friendly: Keras is designed to be user-friendly, making it easy to get started with deep learning.
- Modular: Keras allows for the easy creation of complex models by combining modular components.
- Extensible: You can easily extend Keras by adding new layers, models, and loss functions.
Getting Started
To install Keras, you can use pip:
pip install keras
Example Model
Here's a simple example of a neural network model in Keras:
from keras.models import Sequential
from keras.layers import Dense
model = Sequential()
model.add(Dense(128, input_dim=64, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
Resources
For more information and tutorials, check out the official Keras documentation.
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