prince VS deepirtools

Compare prince vs deepirtools and see what are their differences.

prince

:crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA (by MaxHalford)
Pandas Pca Ca mca Python Svd factor-analysis correspondence-analysis principal-component-analysis scikit-learn multiple-factor-analysis multiple-correspondence-analysis Mfa famd
Source Code
maxhalford.github.io
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deepirtools

Deep learning-based estimation and inference for item response theory models. (by cjurban)
Deep Learning factor-analysis item-response-theory
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prince deepirtools
1 1
1,199 17
- -
7.0 10.0
about 1 month ago over 1 year ago
Python Python
MIT License GNU General Public License v3.0 only
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.
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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.

prince

Posts with mentions or reviews of prince. We have used some of these posts to build our list of alternatives and similar projects.
  • Categorical data in K-means
    1 project | /r/datascience | 19 May 2023
    Well, my favourite thing about posting on Reddit is learning new things. https://github.com/MaxHalford/prince I looked up the Prince and I'll be reading up about FAMD shotly - thanks!

deepirtools

Posts with mentions or reviews of deepirtools. We have used some of these posts to build our list of alternatives and similar projects.
  • [Q] PCA on an all-binary dataset?
    1 project | /r/statistics | 26 Oct 2022
    Agreed, item response theory (IRT) would be a principled approach to use. I recently released a Python package called DeepIRTools that could be helpful here. It uses a deep learning approach to fit IRT models and provides a method for determining the latent dimensionality (i.e., how many "components" to retain). To get the dimension-reduced data (called embeddings in deep learning, factor scores in IRT, and components in PCA), you would just call model.scores(data).

What are some alternatives?

When comparing prince and deepirtools you can also consider the following projects:

orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis

catsim - Computerized Adaptive Testing Simulator

Dask - Parallel computing with task scheduling

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

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.

faceswap - Deepfakes Software For All

privacyIDEA - :closed_lock_with_key: multi factor authentication system (2FA, MFA, OTP Server)

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

mlcourse.ai - Open Machine Learning Course

Keras - Deep Learning for humans

keras - Deep Learning for humans [Moved to: https://github.com/keras-team/keras]

prince vs orange deepirtools vs catsim prince vs Dask deepirtools vs Pytorch prince vs data-science-ipython-notebooks deepirtools vs faceswap prince vs privacyIDEA deepirtools vs transformers prince vs mlcourse.ai deepirtools vs Keras deepirtools vs keras