Deep Learning Platforms
- Concepts
- Computer Science And IT
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Deep Learning Platforms
As machine learning continues to evolve in the implementation of real-time applications with automated features, Deep Learning algorithms have been introduced in order to provide accurate devices when dealing with a huge amount of data. Deep Learning is playing an important role in the operations relevant to the human brain.
There are various deep learning platforms available but need to know what is most suitable according to the consumption of energy and time. You can go through the below mentioned top deep learning platforms and get to know the features that included:
Tensor Flow
Currently, TensorFlow is the most eminent Deep Learning Platform that allows operating the convenient data integration including SQL tables, graphs, and images together. Gmail, Airbnb, Uber, Nvidia, and other top brands are using the TensorFlow deep learning platform due to its powerful computing clusters (Clark, 2019).
Key Features:
• TensorFlow is working with Python as a client language which is the most convenient one. Additionally, other experimenting interfaces also available such as JavaScript, Java, Go, C++, Julia, and C#.
• It requires a lot of coding to provide accurate results according to the assessed dimensions and volume of input and output data.
• It is not only dealing with the powerful computing clusters but also has an ability to run the models on mobile devices like Android and iOS.
• TensorFlow is basically working with a static computation graph that provides efficient outcomes without losing in learning speed.
References:
Clark, D. (2019). Top 16 Open Source Deep Learning Libraries and Platforms. Retrieved from https://www.kdnuggets.com/author/dan-clark