kodi-standalone-service
catboost
| kodi-standalone-service | catboost | |
|---|---|---|
| 2 | 8 | |
| 159 | 7,753 | |
| - | 0.8% | |
| 4.6 | 9.9 | |
| 4 months ago | 2 days ago | |
| Roff | Python | |
| - | Apache License 2.0 |
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kodi-standalone-service
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Telemetry paradox
Setup Kodi with kodi-standalone-service (note: read the readme) so it always runs. Plug your pi into the TV. You can probably use your existing remotes to control Kodi using CEC.
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Running Kodi of a Raspberry Pi w/o desktop environment?
Did you try something like this: https://github.com/graysky2/kodi-standalone-service ?
catboost
- CatBoost: Open-source gradient boosting library
- Boosting Algorithms
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What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms
CatBoost is another popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression.
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Writing the fastest GBDT libary in Rust
Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn.
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Data Science toolset summary from 2021
Catboost - CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. Link - https://catboost.ai/
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CatBoost Quickstart — ML Classification
CatBoost is an open source algorithm based on gradient boosted decision trees. It supports numerical, categorical and text features. Check out the docs.
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[D] What are your favorite Random Forest implementations that support categoricals
If you considering GBDT check out catboost, unfortunately RF mode is not available but library implement lots of interesting categorical encoding tricks that boost accuracy.
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CatBoost and Water Pumps
The data contains a large number of categorical features. The most suitable for obtaining a base-line model, in my opinion, is CatBoost. It is a high-performance, open-source library for gradient boosting on decision trees.
What are some alternatives?
LibreELEC.tv - Just enough OS for KODI
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
glmark2 - glmark2 is an OpenGL 2.0 and ES 2.0 benchmark
Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF)
Kodi Home Theater Software - Kodi is an award-winning free and open source home theater/media center software and entertainment hub for digital media. With its beautiful interface and powerful skinning engine, it's available for Android, BSD, Linux, macOS, iOS, tvOS and Windows.
Keras - Deep Learning for humans
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
pijarr - A shell script to automate the installation and configuration of Jackett, Sonarr, Radarr, Lidarr, Readarr, Prowlarr, and Bazarr on Debian based distros.
vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
hosts - 🔒 Consolidating and extending hosts files from several well-curated sources. Optionally pick extensions for porn, social media, and other categories.
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more