Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
- machine-learning
- deep-learning
- deep-reinforcement-learning
- machine-learning-from-scratch
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
Turns Data and AI algorithms into production-ready web applications in no time.
阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构
Open Machine Learning Course
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
StellarGraph - Machine Learning on Graphs
- graphs
- machine-learning
- machine-learning-algorithms
- graph-convolutional-networks
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
- ai
- fairness-ai
- fairness
- fairness-testing
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
- python
- genetic-algorithm
- optimization
- numpy
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
- visualization
- python3
- python
- xgboost
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
Python-based implementations of algorithms for learning on imbalanced data.
- data-science
- machine-learning
- imbalanced-data
- notre-dame
A fast xgboost feature selection algorithm
- machine-learning
- machine-learning-algorithms
- feature-selection
- xgboost-algorithm
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.
- algorithmic-trading
- cryptocurrency
- ethereum
- moving-average
Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.
- data-science
- model-explanation