Lightning ⚡️ fast forecasting with statistical and econometric models.
- time-series
- statistics
- forecasting
- arima
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Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
Translated词光 (Ciguang, "word light") · Word Atlas — Illustrated IELTS vocabulary with 7,298 words, UK/US audio and FSRS review. Open-source app + CC BY 4.0 dataset.
- chinese
- dataset
- english-learning
- flashcards
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
- machine-learning
- scikit-learn
- statistical-learning
- xgboost
R-CNN: Regions with Convolutional Neural Network Features
Atlas: End-to-End 3D Scene Reconstruction from Posed Images
Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
MatConvNet: CNNs for MATLAB
Natural language detection library for Go
Object detection system using deformable part models (DPMs) and latent SVM (voc-release5). You may want to use the latest tarball on my website. The github code may include code changes that have not been tested as thoroughly and will not necessarily reproduce the results on the website.
Fashion Detection in the Wild (Deep Clothes Detector)
- computer-vision
- deep-learning
- clothes-detection
- clothes-detector
SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Hierarchical Convolutional Features for Visual Tracking (ICCV 2015)
A Network Integration Approach for Drug-Target Interaction Prediction
Natural language detection package in pure Go
- nlp
- natural-language
- language-model
The repository host gives no description.
javascript implementation of the popular snowball word stemming nlp algorithm
R package for segmentation, registration and generating web-based brain atlases from microscope images
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
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.