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RapidMiner AI Hub (BYOL)

RapidMiner | 9.8.0

Linux/Unix, Other CentOS Linux - 64-bit Amazon Machine Image (AMI)

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External reviews

454 reviews
from G2

External reviews are not included in the AWS star rating for the product.


    Alexandre d.

Teaching basic machine learning to students at a university using RapidMiner

  • November 17, 2020
  • Review verified by G2

What do you like best?
Me and the students totally enjoy the ease of creating ML processes and the ability to quickly read in data, easily create processes and instantly have a look at the results. The extension mechanism gives access to useful extensions such as for building RNNs or for NLP. Everything is well explained and there is almost nothing you can't do even with verry little ML background.
Intuitive, Self-Explanatory, Powerful, Useful for ML Explorations, Rapid Prototyping
What do you dislike?
Nothing comes to my mind. I guess if one would want to have more performant executions locally, this tool may not be the fastest option. It builds on top of Deeplearning4j, which has an option to have computations executed using GPUs, but I didn't see this option being propagated to the RapidMiner user.
What problems are you solving with the product? What benefits have you realized?
Teaching ML, Quick Data Explorations, Rapid Prototyping


    John G.

Excellent tool for all levels of data professionals

  • November 01, 2020
  • Review verified by G2

What do you like best?
The ease with which insights can be derived from almost any source of data.
What do you dislike?
It's a bit heavy with the different plugins even though it is expected.
What problems are you solving with the product? What benefits have you realized?
The problem of the lack of insights is solved. The benefits include the ability to read data from almost any datasource.


    Milad A.

How rapid-miner helped me have a better insight of my datasets.

  • October 28, 2020
  • Review provided by G2

What do you like best?
Availability of association rules, supervised learning and deep learning algorithms.
Time series analysis
Covariance
Great data visualization and manipulation tools
User friendly
What do you dislike?
The only thing that I was looking for and did not find was long short term memories and Markov Hidden Models. I believe they are in the verge of creating them as well.
What problems are you solving with the product? What benefits have you realized?
Rule learning from construction schedules
Construction econometrics analysis
Recommendations to others considering the product:
If you are new to any domain of Stats and AI Rapid miner is a very good start
Also it has tools to help experts do their analysis in less time and great quality(presentation-wise)


    Higher Education

RM is a platform suitable for learning and applying Machine Learning

  • October 26, 2020
  • Review verified by G2

What do you like best?
Good, easy to use platform suitable for learning and applying Machine Learning. Interactive GUI and continued efforts by RM to improve product offerings help place RM among the top ML platforms available. Highly recommended!
What do you dislike?
Extensive dataset/ modelling may require high computing power. May be useful to further simplify background code processing to improve speed of generating outputs. However, this is a minor issue. Overall RM is an excellent platform.
What problems are you solving with the product? What benefits have you realized?
I'm in academia. I use RM to teach Machine Learning concepts to students.
Recommendations to others considering the product:
Go try it!


    Julius JR M.

RapidMiner review

  • October 24, 2020
  • Review verified by G2

What do you like best?
It is very intuitive especially to non-coders like myself. They also provided educational licenses for academic institutions which is a big help to further academic use of predictive data analytics and to help foster advances in the academic fields. The RapidMiner community is also very active and helpful. The marketplace also provides useful and timely updates and add-ons which benefit a wide range of needs.
What do you dislike?
There is a slightly steep learning curve for installation and first use. Manuals are also not updated, and newer learning materials (e.g. tutorial videos) should also be updated more regularly.
What problems are you solving with the product? What benefits have you realized?
I mainly use RapidMiner for research purposes. I use most machine learning algorithms to analyze health- and health systems-related parameters, including Covid-19 indices. Using RapidMiner for more than a year has tremendously helped my research activities, and has even sparked new interest in the field of health informatics. Good job to the RapidMiner team!


    Fernando Andres V.

An excellent tool for Data Mining

  • October 23, 2020
  • Review provided by G2

What do you like best?
I used RapidMinner in a Data Mining class, it was an easy program to use and it was easy to find and understand every operator (since everyone had an explanation). In my class we learned the basics but I hope I can use the program even more, I hope to learn more about it.
What do you dislike?
The only problem I found was how to connect the operators sometimes. It takes time to understand that but it`s not impossible.
What problems are you solving with the product? What benefits have you realized?
Since it was a class we used it to build prediction and classification models. I liked that RapidMiner had a lot of operators based on existing models (such as regressions or trees) which could be used to create more complex ones (such as Ridge&Lasso or Random Forest). I haven´t used many softwares for this other than Excel, so another thing I found useful was the Optimize Parameters operator to use different parameters in a single run, which made the job eassier.


    Writing and Editing

Amazing machine learning tool

  • October 20, 2020
  • Review verified by G2

What do you like best?
Excellent platform. System Design very easy to accomplish. An explanation and example of each block diagram could be considered enough to simplify new methods for beginners. It doesn't need deep knowledge to know how to perform things from A to Z.
Before using Rapid Miner I had to spend months to finalize my training and testing phases. I am now able to run experiments and get results in a week.
What do you dislike?
There is a need for more features selection algorithms to be added for a full comparison of designed systems to the state of art methods. The "optimize parameters" block takes some time to run. it forces me many times to restart RapidMiner.
What problems are you solving with the product? What benefits have you realized?
I was able to re-design a machine learning approach for the detection of the autistic population.


    Gabriel N.

The most complete software I have shared with my students

  • October 09, 2020
  • Review verified by G2

What do you like best?
How it works for clustering, one of the favorite tools my students have when I teach data mining.
What do you dislike?
Now days, it requieres so much power from the computer and takes its resources to play, my students have complained about it and I think is one of the reasons why Gartner sent Rapidminer down in the magic quadrant in 2020
What problems are you solving with the product? What benefits have you realized?
One of the problems I solve almost weekly is prescriptive analytics, and it can be done very well with regresion and how it shows.
Recommendations to others considering the product:
Always remember that data mining is the second process in ETL model, so be sure of what you load to RapidMiner so you do not loose time and effort in mining.


    Oliver C.

Very user friendly but error messages could be improved

  • October 09, 2020
  • Review provided by G2

What do you like best?
very intuitive and easy to use. the help community is very fast
What do you dislike?
When plotting graphs, lack of fonts, bold font doesn't show clearly
What problems are you solving with the product? What benefits have you realized?
my data management masters coursework, company project


    Ramesh P.

RapidMiner Supporting Data Science and Machine Learning

  • October 05, 2020
  • Review verified by G2

What do you like best?
RapidMiner is helpful and supportive of data science/analytics life cycle for any data sets. The operators and their list are exhaustive and can be connected per the required design. The tool handles all possible machine learning models right from data cleaning to data preparation to modeling to deploying the models.
As long as the person handling the models using RapidMiner know the process of machine learning activities, how they need to be interconnected, use of various algorithms and their usefulness and limitations the toll provide a great deal of routine work pretty easily, and is very handy for all data scientists and analytics professionals along with business professional.
What do you dislike?
I find some odds using this tool:
AutoML does not seem to handle data from Turbo Prep unless I am missing something here. Also, AuotML process hook ups or connectivity seem to be complicated unnecessarily, the same results are achieved by using simpler operators’ connections.

I worked on a problem where I have two data sets one for training with labels, and the other scoring data set where there is no target variable or target variable need to be predicted. In this scenario I was not able to use AutoML, which only can be used for training the data set. Probably I may be missing something!

-Ramesh Paramkusham, Ph.D
What problems are you solving with the product? What benefits have you realized?
Research and Business problems involving data from finance, technology and other areas from time to time. I like the end-to-end solution supporting data life cycle models such CRISP-DM. Allowing to design models that are generalizable is the key area of benefit that I am looking for in a tool or set of tools such as this one.