What is Ludwig?
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.
Ludwig is a tool in the Machine Learning Tools category of a tech stack.
Ludwig is an open source tool with 7.5K GitHub stars and 886 GitHub forks. Here’s a link to Ludwig's open source repository on GitHub
Who uses Ludwig?
28 developers on StackShare have stated that they use Ludwig.
Python, TensorFlow, Pandas, scikit-learn, and NumPy are some of the popular tools that integrate with Ludwig. Here's a list of all 8 tools that integrate with Ludwig.
Ludwig Alternatives & Comparisons
What are some alternatives to Ludwig?
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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.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.