A unified framework for machine learning with time series
- time-series
- machine-learning
- scikit-learn
- time-series-classification
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The machine learning toolkit for time series analysis in Python
- time-series
- timeseries
- time-series-analysis
- time-series-clustering
A collection of computer vision pre-trained models.
NFStream: a Flexible Network Data Analysis Framework.
- data-science
- data-analysis
- data-mining
- network-analysis
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
mlr3: Machine Learning in R - next generation
- machine-learning
- data-science
- classification
- regression
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
- aifinance
- fintech
- llama
- machine-learning
🎯🗯 Dataset generation for AI chatbots, NLP tasks, named entity recognition or text classification models using a simple DSL!
food image to recipe with deep convolutional neural networks.
- convolutional-neural-networks
- keras
- chef
- deep-learning
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
- deep-learning
- agriculture
- pytorch
- dataset
Crop/Weed Field Image Dataset
- dataset
- crop
- paper
- agriculture
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.
- svm
- regression
- classification
- machine-learning
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
- fine-tuning
- vgg16
- resnet18
- densenet121
Human Protein Atlas image classification competition