Resources
Looking to adopt AI in your manufacturing organization? Start with predictive maintenance – it rises above other use cases in terms of feasibility & impact.
There’s an epidemic that’s preventing models from making it into deployment where they can actually have an impact. RapidMiner illustrates this epidemic.
Machine learning and predictive analytics saved a petrochemical facility a million dollars in through optimizing parameters of a cracked gas compressor loop.
Check out the newest features of RapidMiner 9.3 including better integration with Python for seamless narration & collaboration of models.
In this track we introduce you to all the components of the RapidMiner enterprise platform. You will learn how to deploy them and how to use them for scalable computation, scoring and reporting.
This learning path is the second part of the RapidMiner core training. After taking this, you will be able to perform all common data preparations, build sophisticated analytical predictive models and evaluate model quality with respect to different criteria.
This tutorial pathway is the first part of the RapidMiner & Data Science core training. It can be considered a RapidMiner 101.
Learn how RapidMiner can ease the tension on projects that require collaboration between code-based data scientists and code-free visual approaches being used by citizen data scientists.
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 will walk you through how to use RapidMiner and Text Mining on customer service call transcripts.
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.
This presentation covers how to use sentiment analysis to extract value from context-laden text in a fast, reliable, and objective manner.
This presentation covers how data science tools can be used to advance your process improvement efforts. From HR, Quality, R&D to Finance, data analytics can (and should) be applied internally.
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.
VigiLanz has adopted RapidMiner to integrate machine learning and advanced analytics into its top-ranked clinical decision support suite to detect sepsis early.
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.
Learn about basic concepts of Deep Learning and scenarios that might benefit from its usage, with guidelines for creating networks in a visual way and tips for optimization.
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.
Jeff Dwyer from ezCater discusses how they use RapidMiner to detect the lifetime value of a customer early on in this presentation.
Munwar Shariff from Cappius Technologies / Anblicks demonstrates how RapidMiner can help financial institutions increase revenues and reduce business risk with valuable insights about their customers.
Learn about the role of the business translator and how they can help identify opportunities to use advanced analytics to solve problems.
This track explains the use of RapidMiner Studio and its ecosystem while introducing many of the really important data science concepts at the same time.
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.
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 implementing data analytics in chemical plants can prevent rare events that can lead to the loss of property and potentially life.
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 a water distribution company leverages the insights from RapidMiner to decide where to invest in pipeline rehabilitation & replacement.
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.
Read through this ebook to learn more about Real-Time Scoring use cases for high volume, low latency, and upsell opportunities.
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.
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.
Hadoop offers great promise to organizations looking to gain a competitive advantage from data science. But deploying Hadoop can be extraordinarily complex and time consuming, making it difficult to gain the insights.
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.
Calculating model accuracy is a critical part of any machine learning project, yet many data science tools make it difficult or impossible to assess the true accuracy of a model. Often tools only validate the model selection itself, not what happens around the selection.
In this whitepaper, we discuss how the RapidMiner Platform complies with security standards – providing authentication, authorization, accountability, and data encryption.
RapidMiner Studio 7.4 has added new support for the parallelization of operators, resulting in performance boosts of more than 10x on average.
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.
An analytics division in a privately held healthcare company wanted to use their vast amount of patient treatment data to help drive better care and outcomes. They monitored
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 Mobilkom uses RapidMiner to analyze the textual content of incoming customer requests and automatically determine the topic of each request.
Learn how this manufacturer collects patent documents filed by competitors and uses our text analytics and predictive capabilities to sort and track them.
This multinational pharmaceutical company sells thousands of different drugs. In order to optimize logistical operations and storage needs, the company needed to know future sales.
This giant pharmaceutical firm was looking for customer feedback. It wanted to know what people liked about its products. Did people prefer the company‘s product
Learn how, using RapidMiner, Lufthansa is able to decrease device failures and reduce total downtime by more than 20%, resulting in cost reductions.
RapidMiner offers innovative text analytics solutions that support all of your company’s data needs where textual content is available, needs to be processed or can be analyzed. See how text analytics solutions can help reveal what your customers are thinking.
Learn how this telecommunications company quickly identifies its most valued customer segments, reducing cost of sales and improving revenue opportunities.
This whitepaper outlines the differences between Advanced Analytics and Business Intelligence plus how they fit into the overall category of Analytics.
Learn how to amplify predictive analytics with data visualization and put predictive & prescriptive analytics directly into the hands of every Qlik user.
Get a complimentary copy of the 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. RapidMiner has been identified as a Leader for the 6th year in a row.
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.
Get a complimentary copy of the 2018 Forrester Wave™: Multimodal Predictive Analytics And Machine Learning Solutions
Modern Marketing Concepts, Inc. (MMC) is a global leader in the business-to-business marketing services industry, offering innovative marketing solutions across multiple industries, including the building
Learn how RapidMiner’s features and functionality enable Body Biolytics to process and analyze wearables data quickly, accurately, and intelligently.
Learn how SustainHub uses RapidMiner for risk analysis, checking for errors, flagging certain substances or products, and searching for alternatives.
Data Mining for the Masses is an in-depth eBook that will teach you the basics of data mining with RapidMiner.
Learn how PayPal applies basic voice-of-the-customer-concepts and text analytics to customer feedback to identify, classify, and count their customers.