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Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
deep learning for image processing including classification and object-detection etc.
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Deep neural network to extract intelligent information from invoice documents.
An open source library and framework for deep learning on satellite and aerial imagery.
A curated list of data mining papers about fraud detection.
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
MLBox is a powerful Automated Machine Learning python library.
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
A scikit-learn based module for multi-label et. al. classification
food image to recipe with deep convolutional neural networks.
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.