GLM
github.com/JuliaStats/GLM.jlGLM.jl provides generalized linear models in Julia, with documentation and examples for the package.
Looking for something like DataDeps? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 17 are open source.
DataDeps.jl provides reproducible data setup for scientific work, with a Julia package for fetching and using data dependencies.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | GLM | — | Not stated | — |
| 2 | jSciPy | — | Yes | Android |
| 3 | Dash | — | Yes | — |
| 4 | Piperider | — | Yes | — |
| 5 | AWS Data Wrangler | — | Yes | — |
| 6 | mlxtend | — | Not stated | — |
| 7 | Whylogs | — | Yes | — |
| 8 | DataPrep | — | Yes | — |
| 9 | Tidyverse | — | Not stated | Web |
| 10 | DataComPy | — | Yes | — |
GLM.jl provides generalized linear models in Julia, with documentation and examples for the package.
jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.
Python developers can use Dash to build data apps and dashboards without requiring JavaScript.
PipeRider provided code review tools for dbt data and has been superseded by Recce.
AWS Data Wrangler connects Pandas with AWS data services and databases, including Athena, Glue, Redshift, and S3.
mlxtend adds helper modules for Python data analysis and machine learning libraries.
Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
For Python data preparation, DataPrep offers an open-source low-code library to collect, clean, and visualize data.
The tidyverse is an integrated collection of R packages for data science.
DataComPy compares Pandas, Polars, Spark, and Snowpark dataframes, with output that includes comparison statistics.
SynapseML provides distributed machine learning algorithms for Spark through its Python library.
Koalas implements the pandas DataFrame API on Apache Spark and is deprecated; for Apache Spark 3.2 and above, use PySpark directly.
The Geni project provides a Clojure dataframe library that runs on Apache Spark.
Python developers can use gensim for topic modeling and related natural language processing tasks.
Weights & Biases supports model training, fine tuning, and management from experimentation through production.
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
statsmodels provides statistical modeling and econometrics tools in Python.
GaussianMixtures.jl is a Julia package for working with Gaussian mixture models.
DataFrames.jl provides in-memory tabular data structures and tools for working with data in Julia.
TextAnalysis.jl is a Julia package for text and language data, with tools such as corpora, TF-IDF, and topic models.
ReadStat.jl is a Julia package that parses data files from Stata, SAS, and SPSS into a ReadStatDataFrame.
Valinor maps input data into strongly typed PHP structures without external dependencies.
Distances.jl is a Julia package for calculating distance metrics between vectors, including pairwise and column-wise calculations.
HypothesisTests.jl is a Julia package that implements statistical hypothesis tests.
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