Scikit-learn — the go-to library for machine learning offering a user friendly, consistent interface.
Pycaret — lowering the entry point for machine learning with low code, automated and end to end solutions.
PyTorch — build and deploy powerful, scalable neural networks with its highly flexible architecture.
TensorFlow — one of the most mature deep learning libraries, highly flexible and suited to a wide range of applications.
Keras — TensorFlow made simple.
FastAI — makes deep learning more accessible with a high-level API built on top of PyTorch.
t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. The technique can be implemented via Barnes-Hut approximations, allowing it to be applied on large real-world datasets. We applied it on data sets with up to 30 million examples. The technique and its variants are introduced in the following papers: