Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
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Janus-Series: Unified Multimodal Understanding and Generation Models
- any-to-any
- foundation-models
- llm
- multimodal
Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
Fast and Accurate ML in 3 Lines of Code
Lightning ⚡️ fast forecasting with statistical and econometric models.
- time-series
- statistics
- forecasting
- arima
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
The machine learning toolkit for time series analysis in Python
- time-series
- timeseries
- time-series-analysis
- time-series-clustering
Algorithms for outlier, adversarial and drift detection
- anomaly
- outlier
- concept-drift
- detection
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
A series of machine learning tutorials for Torch7
High-performance, time-indexed object storage for robotics and industrial IoT
- blob-storage
- storage-engine
- storage
- historian
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
- feature-engineering
- machine-learning
- feature
- features
Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
- data-science
- deep-learning
- finance
- financial-data
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.