Webinars & Videos
In Part 2 of this Lightning Demo, Scott Genzer (Data Scientist at RapidMiner) will take the prepared data set from Part 1 and show how to build, validate, and score a multi-horizon forecasting model.
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.
In Part 1 of this Lightning Demo, we’ll begin with a raw industrial time series data set and show how to use RapidMiner to prep the data for modeling including equalizing time stamps, windowing & batching, and more.
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.
Shopping cart analysis and targeted advertising with AI has been a recipe for success for many e-commerce industry titans. Learn how.
It’s important to be able to prevent customer churn in order to generate revenue for your business. In this workshop, you’ll learn how with RapidMiner.
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.
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.
Machine learning architecture needs to scale with data volumes and modeling requirements. In this Lightning Demo, see how RapidMiner AI Hub helps do just that.
Predictive maintenance is a common use case for RapidMiner, particularly in manufacturing. Learn more on connecting OSI PI with RapidMiner.
Businesses need to be agile and consider ways to adjust their pricing strategy to react to economic environment changes, competitor strategies and more. Learn how.
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.
Prescriptive analytics can help us make relevant decisions by providing a better understanding of how to act to change a particular outcome. Learn how.
In order to extract the desired information from unstructured text, data scientists rely on a technique called entity extraction. This session will focus on ways to perform entity extraction in RapidMiner Studio.
Unstructured data presents many challenges in the business world. In this session we will cover how to solve these use cases with document classification techniques in RapidMiner.
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’re doing revenue management without AI, you may be doing it wrong. Join RapidMiner and Revenue.AI for this on-demand webinar.
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 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.
In this series of four videos RapidMiner founder, Ingo Mierswa, demonstrates a complete automated data science project from end to end.
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.
Machine learning and predictive analytics saved a petrochemical facility a million dollars in through optimizing parameters of a cracked gas compressor loop.
Learn how to predict machine failure with RapidMiner and MapR.
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.
“Hey Doc, what Machine Learning model should I use?” In this video, Ingo discusses a simple and proven method for model selection. Deep Learning is not always the best one.
Do you wonder why training a model on your data sometimes takes ages? Learn more about runtimes of data science algorithms in this video with Ingo.
There are two types of black boxes in machine learning. Ingo talks about both types and what needs to be done to get reliable and trustworthy machine learning results.
Here’s a quick video on how facial recognition works with machine learning.
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Learn how your organization can deliver data science and machine learning on Hadoop faster than ever before with RapidMiner and Microsoft Azure and HDInsights.
According to Gartner 72% of manufacturing industry data goes unused due to the complexity of today’s systems and processes. Learn how to take advantage of IoT data in this webinar with MapR.
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.
Watch this webinar with experts from RapidMiner and FICO discussing how to put your analytics into action with a combined framework that simplifies and accelerates model deployment.
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
Learn how we’re addressing the data science skills gap with this radically simple tool to help anyone from an analyst to a data scientist conquer time-consuming data preparation tasks.
RapidMiner Founder Dr. Ingo Mierswa outlines how RapidMiner incorporates a novel approach for automatic feature engineering with RapidMiner Auto Model.
Join RapidMiner Founder Dr. Ingo Mierswa for this webinar on automated machine learning with RapidMiner Auto Model available in RapidMiner 8.1.
RapidMiner Founder and President, Dr. Ingo Mierswa discusses multi-objective optimization in machine learning, as well as, methods for applying it with RapidMiner.
Data Scientist Vladimir Mikhnovich discusses how to overcome the challenges that come with selling data science to your internal stakeholders.
Learn how RapidMiner and Tableau provide a complete solution for analytics teams. See how these two platforms can be applied in manufacturing.
Learn the basics of deep learning with Philipp Schlunder, Data Scientist at RapidMiner. He covers the main components used in creating neural networks.
Building models to predict customer actions is just the first step in implementing data mining and predictive analytics solutions. The integration of the models with
This webinar discusses the trend of the democratization of data science and how that further increases the risk for applying models in a wrong way.
This webinar shows you real world use cases for machine learning on Hadoop using RapidMiner’s new SparkRM capabilities.
Learn how modern predictive analytics helps manage and accelerate all phases of the predictive analytic process lifecycle, from source to result.
Learn how to do process mining with RapidMiner, covering concepts such as process discovery, process conformance analysis, and process performance analysis.
Learn how to build a Sales Pipeline Analysis solution using RapidMiner, removing the bias that plagues traditional forecasting processes.
Watch this webinar to learn the strategies and techniques for integrating Data Science into your Business Intelligence platform.
We’ve put together a list of the top ten most useful tips and tricks from RapidMiner’s data science team, community and super-users. Check it out.
Learn how to dramatically reduce the time spent on basic and advanced data prep tasks such as data exploration, replacing/imputing missing values, replacing nominal/string values, feature generation, handling outliers, and more.
This webinar demos Deep Learning in RapidMiner Studio and discusses the advancements that have transformed what is possible plus the most promising applications.
Learn how to collaborate and share data in a secure and centrally managed environment with RapidMiner Server.
Learn how to leverage machine learning and data science on your available manufacturing or operations data with predictive maintenance.
Many data scientists and analysts don’t have a deep understanding of Hadoop, so they struggle with solving analytics problems in a distributed environment. Watch this webinar to learn best practices for extracting value from Hadoop.
Learn how to amplify predictive analytics with data visualization and put predictive & prescriptive analytics directly into the hands of every Qlik user.
In this webinar we explore the power of social content by analyzing data captured from thousands of tweets referencing Super Bowl 50 ads to determine viewer sentiments.
Data science teams do great work, but it is all for naught if the models they create cannot be operationalized. See how RapidMiner makes it easy for you to build predictive models, and then operationalize them into business systems.