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Figure Eight VS Nilearn

Compare Figure Eight VS Nilearn and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Figure Eight logo Figure Eight

Figure Eight is the essential Human-in-the-Loop Machine Learning platform.

Nilearn logo Nilearn

Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data that leverages the scikit-learn Python toolbox for multivariate statistics.
  • Figure Eight Landing page
    Landing page //
    2023-08-17
  • Nilearn Landing page
    Landing page //
    2023-10-15

Figure Eight videos

+ Add

https://www.youtube.com/watch?v=cPXEIK8N2iE

More videos:

  • Review - 5 Best Sites to Do Figure Eight Tasks to Earn the Most

Nilearn videos

+ Add

Nilearn Dev Days 2020: Sylvia Villeneuve & Carsen Stringer

More videos:

  • Review - Nilearn Dev Days 2020 - Scientific day, Sylvia Villeneuve

Category Popularity

0-100% (relative to Figure Eight and Nilearn)

Figure Eight

Nilearn

Data Science And Machine Learning
95 95%
Data Science And Machine Learning
5% 5
Data Science Tools
100 100%
Data Science Tools
0% 0
Machine Learning
0 0%
Machine Learning
100% 100
Python Tools
100 100%
Python Tools
0% 0

User comments

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Social recommendations and mentions

Based on our record, Nilearn seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Figure Eight mentions (0)

We have not tracked any mentions of Figure Eight yet. Tracking of Figure Eight recommendations started around Mar 2021.

Nilearn mentions (2)

  • [D][R] Image pre-processing for quantitative analysis
    I don't know pyradiomics, it looks interesting. From personal experience I can also recommend the library nilearn (developed by scikit-learn core people) and nipype (and impressive interface to all neuroimaging toolboxes out there. Also, I forgot to mention sMRIprep which is fMRIprpe's little sibling but exclusively for anatomical/structural data. Plus, there's MRIQC, that can extract multiple quality parameters... Source: over 1 year ago
  • Any resources on CNN for neuroimaging?
    The toolbox that you probably might be most interested in is nilearn. It's co-developed by some guys from the scikit-learn team and contains many amazing machine learning routines. CNN might not be the only one you want to look into. Source: about 3 years ago

What are some alternatives?

When comparing Figure Eight and Nilearn, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

OpenCV - OpenCV is the world's biggest computer vision library

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Amazon Rekognition - Add Amazon's advanced image analysis to your applications.

NumPy - NumPy is the fundamental package for scientific computing with Python

Microsoft Video API - Automatically extract metadata from video and audio files using Video Indexer. Improve the performance of your media content with Azure.

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