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.
Scott Genzer developed a technique for using free online facial recognition tools to identify people in photographs. See how it’s applied to historical photos of the Jewish community and beyond.
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.
What exactly do data scientists do? Watch this interview with Scott Genzer, a Data Scientist at RapidMiner, to find out all of the details.
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.
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.
Here’s how to beat the most common data science monsters and get your machine learning model out into the world without getting spooked!
Why is RapidMiner ranked so well among data science and ML platforms? Read this Gartner research report which synthesizes reviews into insights for IT decision makers.
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.
Get a complimentary copy of the 2020 Forrester Wave: Multimodal Predictive Analytics And Machine Learning Solutions
In the Gartner Data Science and Machine Learning Bake-Off, we share RapidMiner’s end-to-end data science capabilities. See it in action.
How do you present a machine learning model to leadership in a way that clearly explains what you did? Here are 5 key questions to consider.
With profit-sensitive scoring, organizations can gain critical insights into the impact that models have on an enterprise’s bottom line. Here’s how.
Don’t just make the best data science decision, make the best business decision. Learn how to create a confusion matrix and better understand your model’s results.
Learn how the usage of sentiment analysis methods and RapidMiner software can help you identifying unfavorable tweets and send a call to action to the affected departments.
RapidMiner 9.7 continues to put people at the center of the AI journey by fostering better collaboration, all while improving the oversight & management. Learn more.
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.
Many use cases require getting predictions in real-time, while maintaining throughput and low latency. Learn how the RapidMiner Real-Time Agent can be used to solve these demanding use cases.
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
Now more than ever, we must maintain our models like we would maintain a machine. Learn the simple steps you can take to make your models resilient during these times of rapid change.
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.
Python is the most popular programming language in the world right now. RapidMiner leverages these cutting edge libraries through scripting operators and also provides integrated JupyterHub. See it in action.
Manufacturers have a wealth of underutilized data that can be used to deliver optimization across their operations. Watch this webinar and learn how to get value from this data to solve critical business problems.
We provide Grafana as a dashboard solution powered by RapidMiner processes. Queries are fired from the dashboard & the data is fetched from RapidMiner in real-time.
Predictive analytics enables marketers to transform data into actionable insights & continuously improve strategies. Here are 10 ways it can be used to drive performance.
The importance and impact of time series analysis and modeling techniques continues to grow. Join us for a 45-minute lightning demo followed by live Q&A on time series foundations.
Time series modeling is a powerful technique that acts as a gateway to understanding and forecasting trends and patterns. Join us for a 45-minute lightning demo on advanced time series.
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!
If you’re doing revenue management without AI, you may be doing it wrong. Join RapidMiner and Revenue.AI for this on-demand webinar.
In this two-part presentation, Lionel demonstrates how to use clustering for preprocessing and how to use clustering for semi-supervised learning.
This presentation demonstrates a new extension that adds the ability for data scientists to make their projects as easily understood as possible.
This presentation discusses the current position of RapidMiner as a tool for personalized medicine and the new era of personalized medicine, genomics, etc.
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.
This session outlines how to use RapidMiner to support investment & maintenance decision-making for linear and networked assets such as pipelines, roads, electric transmission lines, water distribution systems, etc.
An Examination of the NFL Quarterback’s Success: Are athletic intangibles a reliable indicator of success?
Heatherly Carlson explores the relationship between the player intangibles and whether they have ever taken their team to a playoff game.
In this demonstration, Rodrigo explains a proof of concept architecture used to score HTTP requests, detect attackers and block them using RapidMiner Real-Time Scoring.
Our latest 9.6 release expands RapidMiner to full-time coders and BI users. Here we’ll show you the major enhancements made to our data science platform.
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!
This presentation shows the latest advances in RapidMiner that will make it even easier for teams to work together towards the same goal with AI and ML.
This panel brings together different perspectives to discuss how they can best work collaboratively to ensure data science projects have the desired impact.
Overcoming the computational demand of time series: Scaling R-based demand forecasting with RapidMiner
Ryan Frederick of Dominos talks about how his data science team worked through a complex time series forecasting exercise and scaled R-based time models.
FutureBright Analytics: How an international education company uses analytics to power growth and student success at scale
Brian Meagher of Shorelight Education talks about how Shorelight has used data science to help fuel growth and help students succeed.
Brandon Shockley of 160over90 describes the agency’s data-mining journey, from early prototypes to actionable consumer insights.
Muddasir Hassan of Anblicks discusses using artificial intelligence and IoT technology to speed up the fault detection process and predict defects faster.
Jeremy Osinski and Todd Marlin of Ernst and Young discuss how machine learning can help understand and predict employees’ and stakeholders’ intentions.
Mahesh Vinayagam of qBotica discusses the changing landscape of the automation ecosystem, and how enterprises can best use these changes to increase efficiency.
Elise Watson of Clarkston Consulting shows how to use RapidMiner to enhance the health care professional’s journey.
Dr. Mierswa presents a manifesto for data science, a set of basic principles designed to guide our work and make sure that our models have the desired impact.
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!
Get a complimentary copy of the 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms.
In this webinar, we cover the topic of process optimization through the lens of RapidMiner’s virtual optimizer—a real-time prescriptive dashboard that lets workers understand the current state of your operation, experiment with potential changes, and then implement the best solution.
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.
Learn about RapidMiner Managed Server, our services offering to install, configure, and maintain a RapidMiner environment for you.
In this webinar, Ingo dissects the issues that plague organizations striving to become ‘more AI-driven’ and prevent them from executing projects that have the potential to deliver incredible returns.
Looking to adopt AI in your manufacturing organization? Start with predictive maintenance – it rises above other use cases in terms of feasibility & impact.
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.
Machine learning and predictive analytics saved a petrochemical facility a million dollars in through optimizing parameters of a cracked gas compressor loop.
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.
Ingo discusses the need for anew approach to data science, machine learning, and artificial intelligence. Automated machine learning needs to guide analysts and not overrule their decisions.
This session presents a case study demonstrating a risk-based investment decision-making approach supported by machine learning for water distribution system assets.
This presentation shows how to leverage machine learning to detect and prevent fraud and make fraud fighters more efficient and effective.
Master Loyalty Group presents how they created a recommendation system within RapidMiner and the benefits they have seen from doing so.
This presentation covers typical data science roadblocks and how to overcome them, the optimal project structure and timeline for a data science project, and cross-industry examples and success stories of businesses at varying levels of data sophistication.
This presentation discusses Verizon’s Outlier detection system, which uncovers anomalies and then allows for a deep-dive into actionable insights.
This presentation outlines use cases from pure real time reporting to applying predictive analytics. For each use case we will show how they can be implemented using the Streaming Extension and the RapidMiner platform.
This presentation gives an overview of predictive analytics use cases at Lufthansa with some practical use cases from the airline industry like the prediction of arrival times.
The Pegasus Group Company discusses how they monitor and detect the presence of certain pathogens in the oceanic water, alerting the corresponding entities to take action and prevent the spread of these pathogens.
Learn how the Data Scientists teams and IT organization partnered at HPE, providing tools, technologies and processes to close the skill set gap between data science and business roles.
The hype around data science produces a dense fog that can easily restrict the broad scope of your vision, the rising slope of your applications, and the promised hope of new opportunities. This presentation busts those myths and shows you a better, simpler, and more rapid path to value and insights from your data.
Insights Driving Actions: The Role of the Business Translator in Choosing a Use Case with Clarkston Consulting
Learn about the role of the business translator and how they can help identify opportunities to use advanced analytics to solve problems.
Model validation is one of the most important aspects of the data science / machine learning process. In this video we will discuss two widely used visual approaches for comparing model qualities and will focus on how to connect the model with the business value it is supposed to create.
I’ll introduce the concept of hidden black boxes, cover how important understandability is in machine learning, and how to fix black box situations.
Learn how Lufthansa increased the accuracy of their flight arrival time predictions using RapidMiner, saving significant costs associated with delays.
Learn how this manufacturer uses insights from RapidMiner to adjust its operations to reduce customer support costs and improve its customer experience.
Learn how TfL uses RapidMiner for the operation of the road network, managing the traffic signals and ensuring safe, high-quality roadworks across the city.
Learn how a US state auditor leveraged machine learning to detect and prevent the estimated one billion dollars wasted on fraud in healthcare per year.
Learn how the project partners identify huge potential for the application of machine learning to predict product defects early in the production line.
Learn how Daimler and Miele used RapidMiner to accelerate the product design and assembly planning phases in their factories to reduce time and cost.
Learn how LIAT uses RapidMiner to improve the time it takes to respond to customer issues and improve customer sentiment.
Learn how a LDC in the natural gas industry predicts which parts of its pipeline are at the greatest risk of failure with RapidMiner.
Learn how your organization can deliver data science and machine learning on Hadoop faster than ever before with RapidMiner and Microsoft Azure and HDInsights.
Getting actionable insights from unstructured content isn’t easy. Learn how RapidMiner and MonkeyLearn makes it easy to aggregate and analyze your all of your unstructured content.
Jeff Dwyer from ezCater demonstrates how they use Stitch and RapidMiner to make early predictions on LTV – customer lifetime value.
EY shares best practices on how organizations today are blending and drawing correlations from multiple data sources with data science to mitigate and overcome organizational risks.
Working with REST APIs can be cumbersome and challenging, in this webinar we demonstrate how to enrich and analyze chat conversations in RapidMiner Studio.
Learn how to help your marketing team turn customer data into predictions that will increase sales, optimize marketing spend, and make marketing overall more effective.
This webinar details how the partnership between RapidMiner and Talend is helping organizations operationalize predictive models in for use cases such as real-time customer experience, predictive maintenance, and fraud detection.
RapidMiner Data Scientist Dr. Fabian Temme holds a demo on a time series data set where he teaches users how to optimize their forcasting abilities
RapidMiner Founder Dr. Ingo Mierswa outlines how RapidMiner incorporates a novel approach for automatic feature engineering with RapidMiner Auto Model.
In this eBook, RapidMiner Founder and President, Dr. Ingo Mierswa covers: Multi-objective optimization: the secret to great modeling, methods for applying it in machine learning and feature engineering, and how to apply these methods in RapidMiner.
The goal of this book is to introduce you to data science by covering the fundamental concepts plus step-by-step guidance on practical implementations.
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.
Data Science: Concepts and Practice (Second Edition) by Vijau Kotu and Bala Deshpande is now available. Order your copy today.
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 artificial intelligence (AI), machine learning (ML), and big data are changing the renewable energy sector by taking advantage of collected data.
Learn how to structure and analyze customer reviews by sentiment and topic with machine learning and natural language processing.
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.
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.
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.
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.
RapidMiner Founder and President, Dr. Ingo Mierswa discusses multi-objective optimization in machine learning, as well as, methods for applying it with RapidMiner.
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.
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