Deep Learning Library Framework

Overview

Teaching: 20 min
Exercises: 0 min

Questions

• What are Deep Learning Library Framework

Objectives

• Learn different DL Framework

Deep Learning Library Framework

https://www.simplilearn.com/keras-vs-tensorflow-vs-pytorch-article

(1) Keras

• Keras is an effective high-level neural network Application Programming Interface (API) written in Python. This open-source neural network library is designed to provide fast experimentation with deep neural networks, and it can run on top of CNTK, TensorFlow, and Theano.
• Keras focuses on being modular, user-friendly, and extensible. It doesn’t handle low-level computations; instead, it hands them off to another library called the Backend.
• Keras was adopted and integrated into TensorFlow in mid-2017. Users can access it via the tf.keras module. However, the Keras library can still operate separately and independently.

(2) Pytorch

• Pytorch is a relatively new deep learning framework based on Lua Torch.
• Developed by Facebook’s AI research group and open-sourced on GitHub in 2017, it’s used for natural language processing applications.
• Pytorch has a reputation for simplicity, ease of use, flexibility, efficient memory usage, and dynamic computational graphs. It also feels native, making coding more manageable and increasing processing speed.
• Strong competitor to Tensorflow

(3) Tensorflow

• TensorFlow is an end-to-end open-source deep learning framework developed by Google and released in 2015.
• It is known for documentation and training support, scalable production and deployment options, multiple abstraction levels, and support for different platforms, such as Android.
• TensorFlow is a symbolic math library used for neural networks and is best suited for dataflow programming across a range of tasks. It offers multiple abstraction levels for building and training models.

(4) Theano

• Theano used to be one of the more popular deep learning libraries, an open-source project that lets programmers define, evaluate, and optimize mathematical expressions, including multi-dimensional arrays and matrix-valued expressions.
• Theano was developed by the Universite de Montreal in 2007 and is a key foundational library used for deep learning in Python. It’s considered the grandfather of deep learning frameworks and has fallen out of favor by most researchers outside academia.

Conclusions:

• Keras is the easiest Deep Learning Library API. It is easy to transit from Machine Learning based model
• Tensorflow is the most popular DL library developed by Google. It has the most number of user.
• Pytorch is developed by Facebook and gaining significant attention from users all over the world

Key Points

• Keras, Pytorch, Tensorflow