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.

Keras_Tutorial

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 ⚙️

  1. Install Keras:
    pip install tensorflow
    
  2. Import Keras:
    import keras
    
  3. 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. 📘

Neural_Network

Happy coding! 🌟