xgboost_ray
bytehub
Our great sponsors
| xgboost_ray | bytehub | |
|---|---|---|
| 1 | 3 | |
| 131 | 57 | |
| 0.0% | - | |
| 5.8 | 0.0 | |
| about 2 months ago | almost 3 years ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
xgboost_ray
bytehub
- [D] Your 🫵 Preferred Feature Stores?
-
ByteHub: simple timeseries data preparation in Python
Hi everyone! We’ve been building a Python-based feature-store called ByteHub. The aim is to make time series data easy to store, access, and transform when building machine-learning models. It’s available as an open-source library or as a low-cost cloud-hosted service.
- Show HN: Easy-to-use feature store for ML
What are some alternatives?
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
feathr - Feathr – A scalable, unified data and AI engineering platform for enterprise
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
swifter - A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
covalent - Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.