MindsDB VS scikit-learn

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

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MindsDB scikit-learn
16 37
6,901 50,214
9.5% 1.5%
9.9 9.9
7 days ago about 14 hours ago
Python Python
GNU General Public License v3.0 only 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.

MindsDB

Posts with mentions or reviews of MindsDB. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-02.

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 2022-05-08.

What are some alternatives?

When comparing MindsDB 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

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.

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

MLflow - Open source platform for the machine learning lifecycle

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

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