MLBox VS AlphaPy

Compare MLBox vs AlphaPy and see what are their differences.

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MLBox AlphaPy
1 25
1,475 1,052
- 1.9%
0.0 6.7
9 months ago 3 months ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
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.

MLBox

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

AlphaPy

Posts with mentions or reviews of AlphaPy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-23.

What are some alternatives?

When comparing MLBox and AlphaPy you can also consider the following projects:

lazypredict - Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

nylon - An intelligent, flexible grammar of machine learning.

guesslang - Detect the programming language of a source code

draf - Demand Response Analysis Framework (DRAF)

Network-Intrusion-Detection-Using-Machine-Learning - A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

gmr - Gaussian Mixture Regression

sup-res - A great companion for finding key support and resistance levels on financial charts, cryptocurrencies.

ML.NET-Auto-ML-ESRB-Rating-Classification - Classifying Game ESRB Ratings using ML.NET Auto ML

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

deep-kernel-transfer - Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

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.