Caffe2 vs TensorFlow: What are the differences?
Developers describe Caffe2 as "Open Source Cross-Platform Machine Learning Tools (by Facebook)". Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile. On the other hand, TensorFlow is detailed as "Open Source Software Library for Machine Intelligence". TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Caffe2 and TensorFlow can be primarily classified as "Machine Learning" tools.
Caffe2 is an open source tool with 8.46K GitHub stars and 2.13K GitHub forks. Here's a link to Caffe2's open source repository on GitHub.
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What is Caffe2?
What is TensorFlow?
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