Automation is disrupting and displacing old models of production and permanently changing manufacturing. Let’s uncover how we got here and what this new technology means for manufacturers.
Customer churn is a tricky problem to solve. Here we explain the common challenges organizations face and how a machine learning model can help.
Are you new to machine learning and unsure where to started? Read our beginner’s guide covering everything you need to know—what it is, examples, why it’s so valuable and more.
Learn how you can benefit from using Tableau to better visualize and present the work you do in the RapidMiner platform.
If you’re new to data science and aren’t sure where to start, don’t sweat it. Read our beginner’s guide including everything you need to know about applying it to your organization.
Whether you’re a plant manager focused on minimizing product defects or a marketer who wants to predict the results of an upcoming campaign, there’s a good chance that the data
At the DATAcated Conference 2021, experts from a wide range of industries shared great advice for anyone looking to improve how they work with data. Here are some key takeaways.
How is data analytics being used in the food and beverage industry today? Here we’ll dive into 6 of the top use cases that are driving real business impact for these organizations.
Looking to leverage our new Tableau integration? We’ve got you covered. Take a look at how RapidMiner can augment Tableau’s autoML capabilities.
Chemical manufacturers can confront common challenges head on with artificial intelligence. Let’s look at six specific examples of how AI can help.
Let’s look at five examples of how capital-intensive businesses are leveraging AI to improve their bottom lines.
There’s no denying that AI can produce enormous benefits across key areas of insurance. Here are five ways that insurance companies are using it to impact their bottom line.
To make sure that critical aspects are present in your data science work—collaboration and business impact—you need to build an embedded data factory rather than a research institute. Here’s why.
RapidMiner continues to expand the reach of AI and ML by providing plants with the ability to run their own machine learning models. Take a look!
For organizations fortunate enough to have data scientists who code in Python, let’s talk about how you can productively work in a data science platform and the key benefits of doing so.
The automotive industry has begun leveraging new technologies to reshape not only how we drive cars, but also how we conceptualize them. Here are the three biggest technological trends driving the automotive industry in 2021.
We’ve been working hard to expand our platform to meet the needs of larger enterprises, and it’s being recognized! Here’s why we were named a Visionary in the Gartner 2021 Magic Quadrant for Data Science & Machine Learning.
Banking is leading the way in the adoption of artificial intelligence, particularly for risk management. Here are 3 ways that AI helps alleviate risk management functions.
Edge computing refers to a distributed computing framework that aims to process and manage data as close to the source of data generation as possible. Learn the benefits, challenges & more.
What factors have the biggest impact on home purchase prices? Learn to build a machine learning model in RapidMiner Go and share a simulator to easily communicate results.
When done successfully, data modeling plays a vital role in the growth and overall success of almost every business. Here are techniques to help achieve better results.
Learn exactly what industrial internet of things (IIoT) is, and why there’s an even better way forward—the intelligent industrial internet of things.
Learn how AI is being used to help make the holidays merry and bright, even if things are a bit different this year with an ongoing global pandemic.
When it comes to data science, it’s not about what you learn. It’s about what you are able to build with what you know. Find out why.
Machine learning has changed manufacturing forever, and for the better. Here are some of the ways ML will continue to revolutionize the industry in 2021 and beyond.
Learn how artificial intelligence (AI), machine learning (ML), and big data are changing the renewable energy sector by taking advantage of collected data.
Here we’ll introduce you to the In-Database Processing Extension and explain how it can be a very powerful tool under the RapidMiner user’s belt.
Industrial Internet of Things (IIoT) is already transforming manufacturing operations across the globe through several common implementations. Let’s look at some examples.
Here’s how to beat the most common data science monsters and get your machine learning model out into the world without getting spooked!
Automating a data science project can seem overwhelming, but there’s a clear set of steps you can take to ensure that you’re doing things the right way, the first time. Here’s how.
Overall equipment effectiveness (OEE) is a metric used to understand how well manufacturing processes (and equipment) are being used. Learn how to use it to your advantage.
In effort to help manufacturers harness the power of predictive maintenance, we’ll be covering all of the details—what is it, why you need it, how to do it and some examples.
If you’ve ever been confused by the diversity of machine learning algorithms, this post is your path to clarify. Take a look!
With profit-sensitive scoring, organizations can gain critical insights into the impact that models have on an enterprise’s bottom line. Here’s how.
Waiting on perfect data to start a machine learning project is troublesome. Instead, ask yourself what makes data good enough for the project to have an impact. Here’s why.
Keeping college students engaged has often been a struggle for institutions. Learn how to predict students who are at risk of dropping out using advanced data analytics.
There’s no doubt about it—machine learning and artificial intelligence have significantly changed our world over the last few decades. Every day there seems to be a new breakthrough about how AI
Whether you’re new to data science or extremely experienced – mistakes happen. Here we’ll look at some of the most common data science mistakes and how to avoid them.
We’re announcing RapidMiner 9.7, which continues our mission to put people at the center of the AI journey. Get details on the latest enhancements here.
RapidMiner Server is now RapidMiner AI Hub – designed to connect AI to people, processes & technology. But why the change? We explain here.
Heard the buzz about the many benefits of AI, but curious about how it actually delivers? Here are 15 remarkable applications of how companies used AI to transform their business.
Get ahead of inevitable supply chain disruptions and avoid any serious long-term impacts. Here are best practices and tips that organizations should implement today.
Many production processes are done in batches. If your manufacturing organization works this way, you need to be careful in how to use your data. Here’s how to handle it.
Predictive analytics enables marketers to transform data into actionable insights & continuously improve strategies. Here are 10 ways it can be used to drive performance.
Here are a few examples of how humanitarians have leveraged the power of artificial intelligence to assist victims of disasters and others in need.
If you’ve recently found yourself with some extra time on your hands and wanting to improve your data science skills, this post is for you. Take a look!
Python’s popular for machine learning, but it can also have some downsides at the enterprise level. This post explores the pros, cons, and how we can help.
We’re breaking the species barrier in our mission to bring data science to everyone by using the power of data science to improve our pets’ lives.
In supervised learning, model training uses data with known outcomes, while in unsupervised learning, the data doesn’t have a known outcome. So which is best for your use case? Read on to find out!
Let’s become better data scientists by avoiding common pitfalls. Follow these basic principles to make your machine learning projects more impactful.
Resilience is the new accuracy in data science projects. Here’s why your “best” model might not be the best at all…
With Jupyter Notebooks baked into RapidMiner 9.6, coders have a powerful new tool to share projects with coworkers. Read on to find out all the details!
With our latest release, we’re letting anyone shape the future for the better, regardless of their background or skillset. Check out the highlights in this blog post.
Did you miss Wisdom 2020? Or do you want to relive all the fun? This blog post is for you!
What’s coming down the pipe for AI and machine learning in 2020 and beyond?
Natural language processing is changing how companies understand their data. See what it can do for you.
Digital twins are poised to be the next big thing in manufacturing. Learn how they can help support your processes and workflows.
With the holiday season upon us, we wanted to update you about three new features available today in RapidMiner Studio.
Thinking about coming to Boston for our 2020 user conference Wisdom? Here are six of the top things you’ll have FOMO about if you don’t attend.
Detecting model drift is a key component of model impact and maintenance. These tips will help you evaluate drift correctly.
Learn about RapidMiner Managed Server, our services offering to install, configure, and maintain a RapidMiner environment for you.
Learn about two phenomena: change of concept and drift of concept which demonstrate why models can’t just be put into deployment forever.
Organizations are struggling to deliver the promised benefits of data science. We call this the ‘model impact epidemic’ and this post examines the macro trends that allow the epidemic to spread freely.
We are proud to announce 5 new operators added across the Operator Toolbox and Smile extensions. Here’s an overview of these extensions and what’s new.
Data science teams are an evolution of the marketing operations function, who are responsible for marketing technology, processes, and analytics.
RapidMiner Server and Studio can now use the SAML protocol to interact with any identity provider, and incorporate RapidMiner users to the general user management of the company.
If you’ve spent a good bit of time replacing connections while moving a process to production, struggled with collaboration within your team, or have simply found the current feature set too rigid, we have good news for you.
In this article, we cover common issues we encounter when deploying ML models and how the combination of Talend and RapidMiner help overcome them.
Machine learning is constantly making every stage of manufacturing more efficient and lucrative. Learn how to harness its power for your business.
Learn how to connect RapidMiner Auto Model with other applications through Zapier, which has connectors to nearly every application that exists.
Learn how predictive marketing analytics can help engage your audience in all the different stages of a customer journey and maximize lead conversion.
Learn how to structure and analyze customer reviews by sentiment and topic with machine learning and natural language processing.
Here’s a recap of the presentations from the second day of Wisdom 2018 in New Orleans. Wisdom is RapidMiner’s conference for users.
Here’s a recap of the presentations from the first day of Wisdom 2018 in New Orleans. Wisdom is RapidMiner’s conference for users.
What makes data prep so difficult and tedious? Ingo shares his thoughts on this and how RapidMiner addresses this issue with a new data prep approach.
Machine learning and data science have become an intrinsic part of business. Learn how to avoid common data science mistakes that can ruin your business.
RapidMiner regularly releases new versions of RapidMiner Studio, Server and Radoop. Read the top 10 reasons to upgrade to RapidMiner 9.
Read through a demonstration of Turbo Prep and Auto Model by Ingo Mierswa to see how RapidMiner makes data prep and machine learning fun, fast, and simple.
Check out these data science case studies produced by undergraduate students using RapidMiner in an annual data science competition.
One of the most frequent questions I get asked is: “Ingo, I am from Industry X and my data looks like Y and my colleague recommended to use model Z – what is your opinion on what model to use?” In this blog post, I explain a well-proven framework for model selection.
RapidMiner’s Real-Time Scoring Agent extends Server with a lightweight execution engine designed for specific use cases where speed and volume are critical.
Today RapidMiner announced that we’re giving everyone a 30-day trial of Studio Large. Everyone will automatically receive the 30-day trial license.
We are excited to announce our partnership with MapR. This opens up data science possibilities for those who rely on MapR for managing their big data.
RapidMiner Auto Model automates machine learning and accelerates Data Science, making the platform more accessible to new users and more powerful for expert Data Scientists.
In Part 4 of this series we discuss multi-objective feature selection, which can be used for unsupervised learning & to identify best spaces for clusters.
Multi-objective optimization is great for feature selection because we can find all potentially good solutions without defining a trade-off factor.
Evolutionary algorithm is a generic optimization technique mimicking the ideas of natural evolution with the concepts of crossover, mutation, and selection.
Feature selection can greatly improve your machine learning models. Learn about it’s importance in part 1 of this blog series.
Remove obstacles to developing useful machine learning outputs and how to gain insights with the integration of RapidMiner and Tableau.
RapidMiner 8.0 will bring new features that offer improved reliability and horizontal scalability, to which we will expand the platform and revamp Server.
We’ve compiled the top ten most useful tips and tricks from our data science team to help you master our RapidMiner Studio.
Naïve Bayes is a powerful machine learning technique. Learn more about this classifier below and make it part of your standard toolbox.
What exactly are we doing with AI? Learn about what artificial intelligence and machine learning can do – and what it can’t do.
Delano Lima from Brazil won first place for his political tweet analysis project using the Rosette API and Rapidminer Studio in a Data Scientist Challenge.
k-Nearest Neighbors is one of the simplest machine learning algorithms. As for many others, human reasoning was the inspiration for this one as well.
What is data science? Have you read about the relationship between AI, machine learning, and deep learning? How do they relate to data science ?
There is hardly a day where there is no news on artificial intelligence in the media, and people know shockingly little about it. Read to learn more.
Learn more about time series forecasting in RapidMiner Studio and with R. R integrates well within RapidMiner in order to handle time series forecasting.
RapidMiner is a leader in both the Gartner’s Magic Quadrant for Data Science and the Forrester Wave: Predictive Analytics and Machine Learning Solutions.
Customer service centers are dominated by voice interactions between customers and service center agents, who are the face of the company.
Learn how k-fold cross-validation is the go-to method whenever you want to validate the future accuracy of a predictive model.
Learn how k-fold cross-validation is the go-to method whenever you want to validate the future accuracy of a predictive model.
Training errors can be dangerously misleading. Discover which practices will provide you with better estimation techniques for your model.
Data Prep series part 5: Outlier Detection. How to detect outliers and determine whether they are important or erroneous data that needs correction.
Learn how to prevent mistakes in model validation and the necessary components of a correct validation in regards to the training and test error.
Using data visualization can tell a thousand words about your models to stakeholders. Discover how RapidMiner integrates with tools, like Qlik and Tableau.
Feature Generation and Selection is the next step on transforming your data and we have some handy operators to help you make this process fast and easy.
After upgrading RapidMiner Studio, you might be wondering where your processes went. No need to worry, we’ve got you covered!
As Data Scientists, Engineers and Analysts, you have to routinely transform data from one type to another. RapidMiner makes converting data types easy.
Data quality refers to the right type of data being in the right place. Learn how to improve the quality of your data by replacing missing values.
RapidMiner offers the option to export processes as scalable images in the Scalable Vector Graphics (svg) or Portable Document Format (pdf) file formats.
We kicked-off a special-purpose project, named the Data Core Project, to revise the core data management and processing core of RapidMiner.
Now that we have ported the cross-validation operator to make use of parallel execution, you can ultimately produce better results, faster.
You must spend time on data exploration; you must think about the problem you’re trying to solve, bring the right data together and then inspect it.
Learn how to connect with a Remote Desktop and finish the installation of RapidMiner Server on AWS and start running your processes in the cloud.
Learn how to take advantage of the AWS cloud infrastructure environment to put RapidMiner Server in a place where it can run 24/7.
Easily access Federal Reserve Economic Data or FRED API data in RapidMiner Studio using only two operators: Open File and Read XML.
Take advantage of building blocks, pre-built processes encapsulated inside a Subprocess meant to help speed up your analytics.
Learn how to configure Studio settings and add proper path properties to execute R and Python scripts in RapidMiner Server.
Exploring a new discipline is always a difficult task – that’s why we are proud to provide you with a Data Science Map to help you with this journey.
Start a Data Science Project with RapidMiner’s Data Science Expert Marketplace; helping you close the data science skills gap.
If you’re familiar with the Groovy script language, then the Execute Script Operator will quickly become a favorite. Learn more here.
Learn how to use data from MongoDB in RapidMiner to help website owners measure the successes of their online business goals.
The question isn’t RapidMiner vs R, it’s how to use them together. Learn tips and tricks for using RapidMiner with Python and R.
How to join data in RapidMiner. 7 easy ways to mash up your data in SQL fashion without writing SQL and using RapidMiner instead.
Learn how Hadoop big data in-Hadoop & in-memory approaches have positives factors when doing data science.
I wanted to use RapidMiner to tackle Kaggle Competitions and see if I could get in the Top 10% of the ML challenge called “Shelter Animal Outcomes”. – pt.2
I wanted to use RapidMiner to tackle Kaggle Competitions and see if I could get in the Top 10% of the ML challenge called “Shelter Animal Outcomes”.
How do we detect if there’s a problem in our infrastructure? RapidMiner explores the use of customer feedback to predict and reduce IT disruption.
Learn how to use RapidMiner Server to operationalize fraud models, push results to your BI engine, and seamlessly integrate machine learning in your company
Use Machine Learning to understand complex customer behavior patterns. Use RapidMiner to extract those relationships and drive customer retention quickly.
Use data science to predict qualified leads. Use our simple drag and drop data science platform to revolutionize sales and marketing processes.
See why organizations are investing in Qlik machine learning to be able to easily implement predictive analytics models into their business.
Data scientist Martin Schmitz talks about using RapidMiner Studio to do your own cluster analysis of Hearthstone card decks.
Introducing new 7.2 features such as gradient boosted trees, deep learning, generalized linear models, and a brand-new logistic regression.
Similar to Amazon recommendations, RapidMiner shows you which operator other data scientists would use next if they were building your process.
See how text mining with RapidMiner can help you determine customer sentiment, predict trends in adoption and make more informed business decisions.
There’s a lot of ways to use analytics in applications, but you won’t be able to do it efficiently unless you operationalize predictive analytics.
One of the most fun events at Wisdom is our competition, “Who Wants to be a Data Miner?” Participants must design RapidMiner processes for a given goal.
We are embracing an open core business model to strive a good balance between the underlying concepts of open source and letting our organization grow.
Interestingly, a pure open source model has seldom been a successful commercial business model. In fact, maybe the only successful example is RedHat.
You see, things move very fast at RapidMiner. In the past few months we’ve hired 30 new people. And they all have a perspective on “who is RapidMiner.”
RapidMiner Boosts Security, Collaboration & Extensibility in Big Data with Latest Platform Innovations
We’re excited to announce updates to the RapidMiner portfolio. The latest innovations empowers those aiming to get more actionable insight from Big Data.
There are more than 250,000 RapidMiner users worldwide, brilliant minds who have had tasks similar to yours – building some analytical process.
RapidMiner Academia provides free or substantially discounted licenses to students, professors, researchers and other academics.
Explore RapidMiner cloud use cases to help you understand real world applications for running data science processes backed by AWS.
Predictive analytics continues to evolve and the ongoing quest is to build computer systems capable of understanding concepts rather than just keywords.
Radoop, a leading big data analytics solution, makes Hadoop implementations more powerful and easy to use with RapidMiner’s advanced analytics suite.
We believe that our placement in the Leaders quadrant reflects our status as one of the world’s most frequently downloaded predictive analytics tools.
Previously, companies have just analyzed past data to discover what happened, when it happened, and why it happened.
With the news of Rapid-I now being RapidMiner we thought it would be helpful to reiterate that the core of RapidMiner stays open source.
The Rapid-I team keeps on mining and we excavated two great books for our users. The first one, Data Mining for the Masses by Matthew North.
The team is proud to announce the birth of a brand new plot component presenting you a powerful and flexible visualization of your data & process results.
Being not only a company but even an open source company allows us to share this great feeling even more often.
I just stumbled upon this great blog post about some uncommon uses of regular expressions. RapidMiner also makes a lot use of those beasts.
One of the next versions of RapidMiner (5.0.011 or the upcoming version 5.1) will provide a nice extension of the expression parser which is for example used for the operator “Generate Attributes”.
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