Top 10 Open Source Deep Learning Tools in 2022

Top 10 Open Source Deep Learning Tools

1. TensorFlow

  • This model provides an entire end-to-end solution, from construction to deployment
  • Also supports model deployment on embedded devices and mobile devices
  • Documentation and support from the community are key.
  • Support for multiple GPUs
  • Queues and graph visualization
  • Image processing, computer vision, and speech recognition are supported

2. Keras

  • Developer guides and extensive documentation
  • It is easy to use and learn
  • Clear and complete error messages
  • Models for mobile devices, web, and Java Virtual Machine support
  • Distributed deep learning models for graphics processing units (GPUs), and tensor processor units (TPUs).
  • Both in the industry and in research, this principle is widely accepted

3. PyTorch

  • It is widely accepted on major cloud platforms for its ease of development and scalability.
  • Facilitates end-to-end pipeline flow from Python development to mobile device installation (iOS or Android).
  • Industry developers and active researchers provide strong ecosystem libraries that allow development in multiple domains, from reinforcement learning to computer vision.
  • Direct interface to ONNX (open neural network exchange ) compatible systems and environments. Models can be exported in the ONNX standard format
  • Multiple GPU support is available for deep learning models.
  • C++ Interface Supports High Performance and Low Latency Applications
  • Data sharing with libraries externally supported

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
The Tech Trend

The Tech Trend

299 Followers

The Tech Trend is a leading platform of news & information on the latest Tech, Business Growth, Startup, Digital Innovation, Reviews, Fintech, & many more.