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NVivo VS XGBoost

Compare NVivo VS XGBoost and see what are their differences

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Contents:
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  2. » Videos
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NVivo logo NVivo

Buy NVivo now for flexible solutions to meet your specific research and data analysis needs. 

XGBoost logo XGBoost

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.
  • NVivo Landing page
    Landing page //
    2023-06-29
  • XGBoost Landing page
    Landing page //
    2023-07-30

NVivo videos

+ Add

How to use NVivo for your Literature Review Part 1

More videos:

  • Tutorial - NVivo for your literature review- online tutorial
  • Review - Your Dissertation Literature Review Using NVivo

XGBoost videos

+ Add

XGBoost Part 3: Mathematical Details

More videos:

  • Review - XGBoost A Scalable Tree Boosting System June 02, 2016
  • Review - Free Udemy Course - CatBoost vs XGBoost - Classification and Regression Modeling with Python

Category Popularity

0-100% (relative to NVivo and XGBoost)

NVivo

XGBoost

Market Research
100 100%
Market Research
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Text Analytics
100 100%
Text Analytics
0% 0
Business & Commerce
0 0%
Business & Commerce
100% 100

User comments

Share your experience with using NVivo and XGBoost. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, XGBoost seems to be more popular. It has been mentiond 1 time 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.

NVivo mentions (0)

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

XGBoost mentions (1)

  • CS Internship Questions
    By the way, most of the time XGBoost works just as well for projects, would not recommend applying deep learning to every single problem you come across, it's something Stanford CS really likes to showcase when it's well known (1) that sometimes "smaller"/less complex models can perform just as well or have their own interpretive advantages and (2) it is well known within ML and DS communities that deep learning... Source: almost 2 years ago

What are some alternatives?

When comparing NVivo and XGBoost, you can also consider the following products

MAXQDA - a professional software for qualitative and mixed methods data analysis

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

ATLAS.ti - ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data. It offers a variety of sophisticated tools for accomplishing the tasks associated with any systematic approach to "soft" data.

Open Text Magellan - OpenText Magellan - the power of AI in a pre-wired platform that augments decision making and accelerates your business. Learn more.

QualCoder - A very complete Free and Open Source Software (FOSS) Computer-Assisted Qualitative Data Analysis Software (CAQDAS) written in Python. It works with text, images, and multimedia such as audios and videos.

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

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