Data-science-best-resources VS GPBoost

Compare Data-science-best-resources vs GPBoost and see what are their differences.

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Data-science-best-resources GPBoost
2 3
2,768 513
- -
0.0 9.4
4 months ago 5 days ago
C++
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

Data-science-best-resources

Posts with mentions or reviews of Data-science-best-resources. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-13.

GPBoost

Posts with mentions or reviews of GPBoost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-25.

What are some alternatives?

When comparing Data-science-best-resources and GPBoost you can also consider the following projects:

manjaro-linux - Shell scripts for setting up Manjaro Linux for Python programming and deep learning

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.

100-Days-Of-ML-Code - 100 Days of ML Coding

EvalAI - :cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI

cheat-sheet-pdf - 📜 A Cheat-Sheet Collection from the WWW

opentrees - Front end for opentrees.org, a data visualisation of millions of publicly maintained trees around the world.

free-data-science-books - Free resources for learning data science

iNeural - A library for creating Artificial Neural Networks, for use in Machine Learning and Deep Learning algorithms.

IntRo - Introduction to R for health data

frugally-deep - A lightweight header-only library for using Keras (TensorFlow) models in C++.

looper - A resource list for causality in statistics, data science and physics

Cupcake - A Rust library for lattice-based additive homomorphic encryption.