Keras

Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc.

Resources

• Keras Applications - DL models that are made available alongside pre-trained weights. These models can be used for prediction, feature extraction, and fine-tuning
• Transfer Learning Guide: A Practical Tutorial With Examples for Images and Text in Keras

Books

• #BOOK Introduccion practica con Keras (Torres 2018)

Talks

• #TALK Keras, Deep Learning, and the Progress of AI (François Chollet, Lex Fridman Podcast, 2019)

Code

• #CODE Keras
  • http://keras.io/
  • https://keras.io/getting_started/intro_to_keras_for_researchers/
  • Modern Keras design patterns
• #CODE Keras-hub - library that supports natural language processing, computer vision, audio, and multimodal backbones and task models, working natively with TensorFlow, JAX, or PyTorch
• #CODE AutoKeras - Auto-Keras is an open source software library for automated machine learning (AutoML)
  • http://autokeras.com/
  • https://towardsdatascience.com/autokeras-the-killer-of-googles-automl-9e84c552a319
• #CODE Ktrain
  • https://analyticsindiamag.com/a-complete-guide-to-ktrain-a-wrapper-for-tensorflow-keras/

References

• #PAPER Auto-Keras: An Efficient Neural Architecture Search System (Jin 2019)
• #PAPER Applications of Deep Neural Networks with Keras (2022)