Ludwig vs TensorFlow: What are the differences?
Ludwig: A code-free deep learning toolbox, by Uber. Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest; TensorFlow: 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.
Ludwig and TensorFlow can be primarily classified as "Machine Learning" tools.
Ludwig is an open source tool with 4.95K GitHub stars and 526 GitHub forks. Here's a link to Ludwig's open source repository on GitHub.
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