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Top 5 Best Python Deep Learning Libraries
- Theano is a low-level library that specializes in efficient computation. You'll only use this directly if you need fine-grain customization and flexibility.
- TensorFlow is another low-level library that is less mature than Theano. However, it's supported by Google and offers out-of-the-box distributed computing.
- Lasagne is a lightweight wrapper for Theano. Use this if need the flexibility of Theano but don't want to always write neural network layers from scratch.
- Keras is a heavyweight wrapper for both Theano and Tensorflow. It's minimalistic, modular, and awesome for rapid experimentation. This is our favorite Python library for deep learning and the best place to start for beginners.
- MXNet is another high-level library similar to Keras. It offers bindings for multiple languages and support for distributed computing.
- The Mentor: Theano
- The Kid: TensorFlow
- The Augment: Lasagne
- The Cyborg: Keras
- The Polyglot: MXNet
- Theano Documentation - Official documentation and tutorials for Theano.
- Theano Tutorial - Gentle introduction tutorial to Theano.
- TensorFlow Documentation - Official documentation, quickstart guide, and tutorials.
- Learning TensorFlow - Website with tutorials and practical guides.
- Lasagne Documentation - Official documentation and tutorials.
- Adventures Learning Neural Nets and Python - Gentle introduction to using Theano and Lasagne and Theano.
- Keras Documentation - Official documentation, quickstart guide, and tutorials.
- "Hello World" in Keras - Gentle introduction to Keras using the Iris dataset.
- MXNet Documentation - Official documentation and tutorials.
- Getting Started with MXNet - Gentle introduction to MXNet and its paradigms.