MonkeyLearn is a Text Analysis platform that allows companies to create new value from text data.
$299
per month
RapidMiner
Score 8.9 out of 10
N/A
RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
Text analysis tools. Thanks to its more than 60 native integrations in the platforms, they make it possible to import your data sets. Furthermore, they also make it easy to export your data sets to other programs. Built-in extensions make their flexible platforms. Some of these …
I have used MonkeyLearn to analyze texts and extract information, that has been a tough task for me because I have to do it manually, but this software has made it easy for me, it is very easy to use and very intuitive, I can use it for extracting information from emails, chats, forums, websites, etc. I would definitely recommend using this platform to others.
RapidMiner is really fantastic to perform fast ETL processes and work on your data as you want, no matter what is the source. You will really save a lot of time when you learn how to use it. You can create mining analysis with several algorithms, and thanks to add-ons, you can apply a lot of techniques. It will not replace a business intelligence dashboard but it allows to create great datamarts for your BI tools. One negative thing is that It's no easy to share your outputs.
I like how MonkeyLearn can track customer feedback for us, it helps us get more data about customer needs, it makes it easier for us to analyze customer feedback and act on it in the future.
Easily build and train a machine learning model to tag and classify your text.
I am very impressed at how easily you can work within RapidMiner without much data analytics training. Plus with the help of the crowd, you can see what steps others have taken with their data analytics projects.
Text mining was simple and clean. We used this for our call transcription problem where we didn't have the resources to listen to each call. We needed to qualify each call based on some key phrases.
Our direct mail program was large and not very targeted. Using RapidMiner, we were able to isolate a predictive level we felt comfortable with and decided not to send to anyone below that level. We saved quite a bit of money.
I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates.
Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model.
More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples.
Text analysis tools. Thanks to its more than 60 native integrations in the platforms, they make it possible to import your data sets. Furthermore, they also make it easy to export your data sets to other programs. Built-in extensions make their flexible platforms. Some of these integrations include word processing, detection, and web mining.
We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and user-friendly.
Thanks to the patters that RapidMiner has detected, we have been able to follow clues in the right direction, both for the Protein Interaction Network Analysis and for the Epilepsy Research
Students and participants of the machine learning workshops have learned about this technology and about the tool