A repository of material for the exercise classes of a Big Data Analytics master course. Hands-on sessions cover Spark and its machine learning library, Map/Reduce implementations of linear regression and alternating least squares, streaming analytics with Recursive Least Squares, and image classification with convolutional neural networks. Material is provided as Jupyter notebooks.
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github.com
Project that automatically maps relationship networks by parsing public data using LLMs and visualizes it as an interactive graph.
cse.unr.edu
Personal page of Hakan Kardes, a principal scientist whose listed research interests include big data, record linkage, data mining, graph theory, social networks and Internet measurements. The page lists publications on topics such as connected component computation in MapReduce, address parsing and organization entity resolution.
github.com
NeuPy is a Python library built on Tensorflow for prototyping and building neural networks. The repository notes that the library is no longer actively maintained. It includes examples and notebooks covering algorithms such as Boltzmann machines and self-organizing maps.
github.com
Zetane Viewer is a free tool for visualizing machine learning and artificial neural network models, including architecture and internal data such as feature maps, weights, biases and layer output tensors. The viewer supports .ONNX and .ZTN files and is available for Windows, Linux and Mac. It can also be launched from existing scripts or notebooks via the Zetane Python API.