The best free and open-source automated time tracker. Cross-platform, extensible, privacy-focused.
- quantified-self
- activitywatch
- productivity
- time-tracking
Repository Index
47,133 repositories indexed
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An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
A standalone embedding of the FOSS drawio / mxgraph package into jupyterlab
A C++ header-only library of statistical distribution functions.
- stats
- cpp
- constexpr
- numerical-methods
The foundational library of the Morpheus data science framework
- datascience
- data-analysis
- data-analytics
- regression
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
- quantum-mechanics
- materials-informatics
- data-science
- machine-learning
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization
Quantitative Economics
Compilado de recursos sobre Computação Quântica em português
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
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
Streaming-first technical indicators with a Rust core: native Python, Node.js and WebAssembly bindings plus a C ABI hub for C, C++, C#, Go, Java and R. 514 indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement.
- algotrading
- backtesting
- bollinger-bands
- cryptocurrency
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
Research experiments exploring uncommon quant techniques.
- analysis
- jupyter-notebook
- python
- quant
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
Personal website
- r
- tidymodels
- tidyverse
- quarto
💸 Papers and Code Implements for Quantitative-Trading
Quanfima (Quantitative Analysis of Fibrous Materials)
- data-analysis
- material-science
- volumetric-data
- morphological-analysis
Analysis of TrackMate XML outputs in R
C++ backend for the jupyter webrtc widget
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
A demonstration tutorial of using aiida-quantumespresso