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Top 23 Python Xgboost Projects
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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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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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m2cgen
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
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mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
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AutoViz
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
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MLServer
An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
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Auto_ViML
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
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Hyperactive
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
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alpha-zero-boosted
A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
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Python-Schema-Matching
A python tool using XGboost and sentence-transformers to perform schema matching task on tables.
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quick-deploy
Optimize, convert and deploy machine learning models as fast inference API using Triton and ORT. Currently support Hugging Face transformers, PyToch, Tensorflow, SKLearn and XGBoost models.
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Rating-Correlations
Predicts chess960 or crazyhouse ratings given bullet or blitz and others for either Lichess.org or Chess.com servers.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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.
Check out: https://github.com/BayesWitnesses/m2cgen
MLForecast
Project mention: Show HN: A gallery of dev tool marketing examples | news.ycombinator.com | 2023-10-07Hi I am Jakub. I run marketing at a dev tool startup https://neptune.ai/ and I share learnings on dev tool marketing on my blog https://www.developermarkepear.com/.
Whenever I'd start a new marketing project I found myself going over a list of 20+ companies I knew could have done something well to “copy-paste” their approach as a baseline (think Tailscale, DigitalOCean, Vercel, Algolia, CircleCi, Supabase, Posthog, Auth0).
So past year and a half, I’ve been screenshoting examples of how companies that are good at dev marketing do things like pricing, landing page design, ads, videos, blog conversion ideas. And for each example I added a note as to why I thought it was good.
Now, it is ~140 examples organized by tags so you can browse all or get stuff for a particular topic.
Hope it is helpful to some dev tool founders and marketers in here.
wdyt?
Also, I am always looking for new companies/marketing ideas to add to this, so if you’d like to share good examples I’d really appreciate it.
Project mention: Introduction to Thompson Sampling: The Bernoulli Bandit | news.ycombinator.com | 2024-02-04I built a contextual bandit combining XGBoost with Thompson Sampling you can check out at https://improve.ai
Python Xgboost related posts
- Show HN: A gallery of dev tool marketing examples
- How to structure/manage a machine learning experiment? (medical imaging)
- How to grow a developer blog to 3M annual visitors? with Jakub Czakon (Neptune.ai)
- [D] Is there any all in one deep learning platform or software
- New Data Scientist, want to get into MLOps, where to start?
- Does a fully sentient (Or at least as sentient as you and me) AI with free will have a soul?
- [D] The hype around Mojo lang
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A note from our sponsor - InfluxDB
www.influxdata.com | 25 Apr 2024
Index
What are some of the best open-source Xgboost projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | kserve | 3,047 |
2 | mljar-supervised | 2,929 |
3 | m2cgen | 2,707 |
4 | mars | 2,675 |
5 | AutoViz | 1,621 |
6 | MLBox | 1,475 |
7 | xorbits | 1,002 |
8 | awesome-gradient-boosting-papers | 980 |
9 | mlforecast | 713 |
10 | MLServer | 568 |
11 | neptune-client | 531 |
12 | FastTreeSHAP | 492 |
13 | Auto_ViML | 490 |
14 | Hyperactive | 487 |
15 | xgboost_ray | 131 |
16 | tempo | 111 |
17 | alpha-zero-boosted | 79 |
18 | Python-Schema-Matching | 23 |
19 | python-ranker | 21 |
20 | dmatrix2np | 17 |
21 | quick-deploy | 6 |
22 | Language_Identifier | 1 |
23 | Rating-Correlations | 1 |
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