Machine Learning¶

The following Python libraries are available:

scikit-learn is one of the most popular ML libraries for classical ML algorithms. It offers a broad range of clustering, regression and classification algorithms. DBSCAN, gradient boosting, random forests, vector machines, and k-means are a few examples. It can interoperate with numeric and scientific libraries of Python like NumPy and SciPy.
TensorFlow is a library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. TensorFlow can handle deep neural networks for image recognition, handwritten digit classification, recurrent neural networks, NLP (Natural Language Processing), word embedding and PDE (Partial Differential Equation).
PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.

The following table lists the available versions of each of these libraries.

Other libraries like numpy and pandas are kept up to date as long there are no conflicts with the packages above.

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