Software Alternatives & Reviews

RapidMiner VS R Caret

Compare RapidMiner VS R Caret and see what are their differences

RapidMiner logo RapidMiner

RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

R Caret logo R Caret

Documentation for the caret package.
  • RapidMiner Landing page
    Landing page //
    2022-06-12
Not present

RapidMiner videos

RapidMiner Review - Predictive analytics software review

More videos:

  • Review - Analyzing Customer Reviews with MonkeyLearn and RapidMiner
  • Review - SENTIMENT ANALYSIS OF MOVIE REVIEW USING RAPIDMINER FROM EXCEL FILE

R Caret videos

No R Caret videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to RapidMiner and R Caret)
Data Science And Machine Learning
Data Science Tools
100 100%
0% 0
AI
0 0%
100% 100
Python Tools
100 100%
0% 0

User comments

Share your experience with using RapidMiner and R Caret. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare RapidMiner and R Caret

RapidMiner Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: RapidMiner offers a data science platform that enables people of all skill levels across the enterprise to build and operate AI solutions. The product covers the full lifecycle of the AI production process, from data exploration and data preparation to model building, model deployment, and model operations. RapidMiner provides the depth that data scientists...

R Caret Reviews

We have no reviews of R Caret yet.
Be the first one to post

Social recommendations and mentions

Based on our record, RapidMiner seems to be more popular. It has been mentiond 3 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.

RapidMiner mentions (3)

  • I need help lol
    RapidMiner: A data science platform that offers an automated EDA process, including data preprocessing, visualization, and analysis. Source: about 1 year ago
  • Intro to Py-Arrow
    I hope this blog empowers you to start digging deeper into Apache Arrow and helps you to understand why we decided to invest in the future of Apache Arrow and its child products. I also hope it gives you the foundations to start exploring how you can build your own analytics applications from this framework. InfluxDB’s new storage engine emphasizes its commitment to the greater ecosystem. For instance, allowing... - Source: dev.to / about 1 year ago
  • Data Science toolset summary from 2021
    Rapidminer - RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics. Link - https://rapidminer.com/. - Source: dev.to / over 2 years ago

R Caret mentions (0)

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

What are some alternatives?

When comparing RapidMiner and R Caret, 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.

H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

R MLstudio - The ML Studio is interactive for EDA, statistical modeling and machine learning applications.

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

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