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Top 23 feature-engineering Open-Source Projects
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
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metarank
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
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SGX-Full-OrderBook-Tick-Data-Trading-Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
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SaaSHub
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OpenMLDB
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
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hamilton
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
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Deep_Learning_Machine_Learning_Stock
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
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NVTabular
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
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functime
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
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intelligent-trading-bot
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
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temporian
Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖
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Hyperactive
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
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serverless-ml-course
Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
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desbordante-core
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
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SaaSHub
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Project mention: Featuretools – A Python Library for Automated Feature Engineering | news.ycombinator.com | 2023-09-20
Project mention: Show HN: Web App with GUI for AutoML on Tabular Data | news.ycombinator.com | 2023-08-24Web App is using two open-source packages that I've created:
- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised
- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury
You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.
Project mention: HFT: High frequency trading. Extended Research - star count:1469.0 | /r/algoprojects | 2023-07-08
Project mention: OpenMLDB v0.9.0 Release: Major Upgrade in SQL Capabilities Covering the Entire Feature Servicing Process | dev.to | 2024-05-02For detailed release notes, please refer to: https://github.com/4paradigm/OpenMLDB/releases/tag/v0.9.0
Project mention: Show HN: Hamilton's UI – observability, lineage, and catalog for data pipelines | news.ycombinator.com | 2024-05-02
Project mention: Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:1017.0 | /r/algoprojects | 2023-12-10
I agree that the conventional (numeric) forecasting can hardly benefit from the newest approaches like transformers and LLMs. I made such a conclusion while working on the intelligent trading bot [0] by experimenting with many ML algorithms. Yet, there exist some cases where transformers might provide significant advantages. They could be useful where the (numeric) forecasting is augmented with discrete event analysis and where sequences of events are important. Another use case is where certain patterns are important like those detected in technical analysis. Yet, for these cases much more data is needed.
[0] https://github.com/asavinov/intelligent-trading-bot Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
Project mention: Temporian: Google's Python package for time series preprocessing | news.ycombinator.com | 2024-02-13
feature-engineering related posts
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protr VS seqinr - a user suggested alternative
2 projects | 5 May 2024 -
OpenMLDB v0.9.0 Release: Major Upgrade in SQL Capabilities Covering the Entire Feature Servicing Process
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Comparative Analysis of Memory Consumption: OpenMLDB vs Redis Test Report
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Ultra High-Performance Database OpenM(ysq)LDB: Seamless Compatibility with MySQL Protocol and Multi-Language MySQL Client
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Mastering Distributed Database Development in 10 Minutes with OpenMLDB Developer Docker Image
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Temporian: Google's Python package for time series preprocessing
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OpenMLDB new release v0.8.4
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A note from our sponsor - SaaSHub
www.saashub.com | 10 May 2024
Index
What are some of the best open-source feature-engineering projects? This list will help you:
Project | Stars | |
---|---|---|
1 | nni | 13,765 |
2 | featuretools | 7,035 |
3 | mljar-supervised | 2,941 |
4 | metarank | 1,988 |
5 | feathr | 1,931 |
6 | SGX-Full-OrderBook-Tick-Data-Trading-Strategy | 1,749 |
7 | featureform | 1,705 |
8 | OpenMLDB | 1,550 |
9 | hamilton | 1,373 |
10 | Deep_Learning_Machine_Learning_Stock | 1,149 |
11 | hopsworks | 1,087 |
12 | NVTabular | 1,008 |
13 | functime | 914 |
14 | tsfel | 860 |
15 | intelligent-trading-bot | 748 |
16 | evalml | 713 |
17 | temporian | 625 |
18 | deltapy | 527 |
19 | Hyperactive | 490 |
20 | serverless-ml-course | 485 |
21 | tsflex | 363 |
22 | desbordante-core | 354 |
23 | hrv-analysis | 349 |
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