python-recsys VS scikit-learn

Compare python-recsys vs scikit-learn and see what are their differences.

python-recsys

A python library for implementing a recommender system (by ocelma)

scikit-learn

scikit-learn: machine learning in Python (by scikit-learn)
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python-recsys scikit-learn
0 30
1,406 48,629
- 1.1%
0.0 9.9
about 1 year ago about 12 hours ago
Python Python
http://www.gnu.org/copyleft/gpl.html BSD 3-clause "New" or "Revised" License
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.

python-recsys

Posts with mentions or reviews of python-recsys. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning python-recsys yet.
Tracking mentions began in Dec 2020.

scikit-learn

Posts with mentions or reviews of scikit-learn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-17.

What are some alternatives?

When comparing python-recsys and scikit-learn you can also consider the following projects:

Keras - Deep Learning for humans

Surprise - A Python scikit for building and analyzing recommender systems

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

tensorflow - An Open Source Machine Learning Framework for Everyone

gensim - Topic Modelling for Humans

PyBrain

TFLearn - Deep learning library featuring a higher-level API for TensorFlow.

seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

MLflow - Open source platform for the machine learning lifecycle

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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