Welcome to the Keras Tutorial! 🚀
Keras is an open-source library for building and training deep learning models, known for its user-friendly API and flexibility. Below is a quick overview to get you started:
What is Keras? 🤖
Keras simplifies the process of creating neural networks by abstracting complex operations. It runs on top of TensorFlow, Theano, or CNTK, making it versatile for different deep learning tasks.
Key Features 📌
- Modular & Extensible: Build models using layers and modules.
- Seamless Integration: Works with TensorFlow, Theano, and CNTK.
- Pre-trained Models: Access models like VGG16 or ResNet50 via
keras.applications
. - Easy Debugging: Real-time visualization with tools like TensorBoard.
Getting Started ⚙️
- Install Keras:
pip install tensorflow
- Import Keras:
import keras
- Build a Simple Model:
model = keras.Sequential([ keras.layers.Dense(10, input_shape=(None, 5)), keras.layers.Activation('softmax') ])
Applications 🌍
Keras is widely used in:
- Image classification
- Natural Language Processing (NLP)
- Time series analysis
- Generative models (e.g., GANs)
For more advanced topics, check out our Keras Documentation. 📘
Happy coding! 🌟