Resources
Industrial Time Series Analysis – Part 2
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.
Digital Engagement and Sentiment Analysis with Lufthansa Industry Solutions
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.
Industrial Time Series Analysis – Part 1
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.
Stop waiting for perfect data
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.
What’s New in RapidMiner 9.7: Making AI a Team Sport
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.
Spotlight: Identifying students at risk of dropping out
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.
Market Basket Analysis in RapidMiner
Shopping cart analysis and targeted advertising with AI has been a recipe for success for many e-commerce industry titans. Learn how.
Solving Customer Churn: A Telecom Use Case
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.
Low Latency/Edge/Real-Time Scoring using RapidMiner Real-Time Agent
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.
10 surprising applications of machine learning in everyday life
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
Drift Management and Model Resiliency for the Ever-Changing World
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.
4 common data science mistakes you don’t want to make
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.
Multi Node ETL and ML Jobs with RapidMiner AI Hub
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 in RapidMiner with OSI PI
Predictive maintenance is a common use case for RapidMiner, particularly in manufacturing. Learn more on connecting OSI PI with RapidMiner.
Announcing RapidMiner 9.7 — Making data science a team sport
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 — Why the change?
RapidMiner Server is now RapidMiner AI Hub – designed to connect AI to people, processes & technology. But why the change? We explain here.
Revenue Management
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.
15 remarkable applications & examples of AI in business
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 and RapidMiner’s Jupyter Notebook Integration
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.
How to prepare for supply chain disruptions
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.
Optimizing Operations with Collaboration for Success
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.
50 Ways to Impact Your Business with AI
Looking to drive real business impact with AI? Get inspired by these 50 AI use cases that we’ve compiled from across all industries.
Deploy Prescriptive Models Using Interactive Dashboards
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.
Gartner Research Report: Five Ways Artificial Intelligence and Machine Learning Deliver Business Impacts
Read this Gartner research report detailing how organizations can deliver real business impact through AI and machine learning. Download your copy.
Handling batch production data in manufacturing
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.
Prescriptive Optimizer
Prescriptive analytics can help us make relevant decisions by providing a better understanding of how to act to change a particular outcome. Learn how.
Building the Perfect AI Team
What functional roles are needed for a successful machine learning project? This ebook provides guidance on how to go about building your AI dream team.
Text Mining – Entity extraction
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.
How to use predictive analytics for better marketing
Predictive analytics enables marketers to transform data into actionable insights & continuously improve strategies. Here are 10 ways it can be used to drive performance.
Text Mining – Document classification
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.
Doing good with machine learning and AI
Here are a few examples of how humanitarians have leveraged the power of artificial intelligence to assist victims of disasters and others in need.
RapidMiner Platform Brochure
Read our platform brochure to learn more about how RapidMiner unifies the entire data science lifecycle from data prep, to machine learning and model operations.
Time Series Foundations – Univariate time series forecasting
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.
Advanced Time Series – Multivariate time series forecasting
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.
8 best online courses & certifications for data science
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!
AI and Intelligent Assistants for Revenue Management
If you’re doing revenue management without AI, you may be doing it wrong. Join RapidMiner and Revenue.AI for this on-demand webinar.
The pros and cons of Python for enterprises
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.
A New Python Operator Framework
RapidMiner’s own Head of Data Science Martin Schmitz gives an overview of the new Python Operating Framework in this presentation.
Clustering as Part of the Data Science Methodology
In this two-part presentation, Lionel demonstrates how to use clustering for preprocessing and how to use clustering for semi-supervised learning.
The Web App Builder Extension: A new way of deploying machine learning projects using web apps
This presentation demonstrates a new extension that adds the ability for data scientists to make their projects as easily understood as possible.
New Tools from RapidMiner Labs
In this presentation, Gisa demonstrates her brand new extension that creates a code-free method of taking a process and wrapping it into an extension.
Post “One-Size-Fits-All” Healthcare: Welcome to the new era of personalized medicine
This presentation discusses the current position of RapidMiner as a tool for personalized medicine and the new era of personalized medicine, genomics, etc.
Making the impossible paw-ssible: Introducing data science for cats and dogs
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.
Using RapidMiner to Support Capital & Maintenance Decision Making for Linear and Networked Assets
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.
Better Together: RapidMiner and Tableau
This session is a demonstration of the RapidMiner-Tableau Integration component developed by Bhupendra Patil of RapidMiner for classification and association mining.
Teaching Rapidly: Using RapidMiner in education
In this session, Tamilla Triantoro presents how she adopted RapidMiner for teaching machine learning concepts, including topics and techniques she covered in class, student feedback, and the support she received from RapidMiner unicorns.
Data Mining for the Masses 4th Edition eBook Demo
This presentation reviews the latest enhancements to the book, now published in its fourth edition as an interactive, smart textbook on the MyEducator platform.
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.
Data Science for Cybersecurity: Identifying and mitigating threats with RapidMiner
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.
RapidMiner 9.6: Expanding RapidMiner to full-time coders and BI users
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.
Supervised vs. unsupervised machine learning: What’s the difference?
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!
AI for Anyone: The RapidMiner vision that puts people at the center of artificial intelligence
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.
Getting Data Science Projects Over the Finish Line
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.
Finding the Story: How a global creative agency tapped into data science
Brandon Shockley of 160over90 describes the agency’s data-mining journey, from early prototypes to actionable consumer insights.
Enhancing Quality Control & Transforming Industry 4.0 with AI & IoT
Muddasir Hassan of Anblicks discusses using artificial intelligence and IoT technology to speed up the fault detection process and predict defects faster.
Call Volume Forecast Using RapidMiner
Michael Stansky of FirstEnergy demonstrates how to use RapidMiner to forecast customer contact center call volume using historical all volume and considering call volume drivers.
Bridging the Gap: Measuring & enhancing integrity with data science
Jeremy Osinski and Todd Marlin of Ernst and Young discuss how machine learning can help understand and predict employees’ and stakeholders’ intentions.
We Need Smarter Bots: The rapid evolution of the automation ecosystem
Mahesh Vinayagam of qBotica discusses the changing landscape of the automation ecosystem, and how enterprises can best use these changes to increase efficiency.
Using the full RapidMiner Platform to Improve Sales & Marketing for the Customer Journey
Elise Watson of Clarkston Consulting shows how to use RapidMiner to enhance the health care professional’s journey.
Deepfake is for Losers (and other secret confessions of a data scientist)
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.
A manifesto for data science
Let’s become better data scientists by avoiding common pitfalls. Follow these basic principles to make your machine learning projects more impactful.
Model accuracy isn’t enough: You need resilient models
Resilience is the new accuracy in data science projects. Here’s why your “best” model might not be the best at all…
Snakes in space: Unleashing the power of Jupyter Notebook and Python in RapidMiner
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!
Putting people at the center of AI: RapidMiner 9.6
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.
Impact, explainability, and resilience — Themes from Wisdom 2020
Did you miss Wisdom 2020? Or do you want to relive all the fun? This blog post is for you!
Gartner Magic Quadrant for Data Science and Machine Learning Platforms
Get a complimentary copy of the 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms.
RapidMiner Virtual Optimizer
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.
5 AI predictions for 2020 and beyond
What’s coming down the pipe for AI and machine learning in 2020 and beyond?
5 business applications for natural language processing
Natural language processing is changing how companies understand their data. See what it can do for you.
Digital twins for fun and profit
Digital twins are poised to be the next big thing in manufacturing. Learn how they can help support your processes and workflows.
Your Path to Fully Automated Data Science
In this series of four videos RapidMiner founder, Ingo Mierswa, demonstrates a complete automated data science project from end to end.
A Human’s Guide to Machine Learning Projects
Getting a machine learning project off the ground is hard. How do you build a solid project foundation from the very start? Download the whitepaper.
Caching and unwrapping some holiday joy
With the holiday season upon us, we wanted to update you about three new features available today in RapidMiner Studio.
Six reasons you should attend Wisdom 2020
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.
How to Detect Drifting Models
Detecting model drift is a key component of model impact and maintenance. These tips will help you evaluate drift correctly.
How to operationalize data science and machine learning without IT hurdles
Learn about RapidMiner Managed Server, our services offering to install, configure, and maintain a RapidMiner environment for you.
How to Cure the Model Impact Epidemic: A Path to Sustainable AI in Simple Terms
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.
Why Your Models Need Maintenance
Learn about two phenomena: change of concept and drift of concept which demonstrate why models can’t just be put into deployment forever.
6 Trends Causing the Model Impact Epidemic
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.
Predictive Maintenance – A Powerful First Step Towards Adopting AI for Manufacturing
Looking to adopt AI in your manufacturing organization? Start with predictive maintenance – it rises above other use cases in terms of feasibility & impact.
The Model Impact Epidemic
There’s an epidemic that’s preventing models from making it into deployment where they can actually have an impact. RapidMiner illustrates this epidemic.
5 New Operators Added Across the Operator Toolbox and Smile Extensions!
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.
How to Build a Data-Driven Marketing Team
Data science teams are an evolution of the marketing operations function, who are responsible for marketing technology, processes, and analytics.
Price Optimization
Machine learning driven price optimization is reshaping industries from hotels to retail. Learn what it is what it can do for you.
Delivering Value Through Predictive Analytics in Chemical Process Industries
Machine learning and predictive analytics saved a petrochemical facility a million dollars in through optimizing parameters of a cracked gas compressor loop.
RapidMiner and Enterprise Authentication
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.
How to manage your data connections, speed up deployment and improve collaboration
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.
Data Mining Tools
Data mining tools are used to uncover patterns inside large sets of data to predict future outcomes. Learn more about data mining with RapidMiner.
Code-Free and Code-Based Data Science
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.
No Magic Wands: The Benefits and Dangers of Automated Machine Learning
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.
Using Text Mining to Improve Customer Service
This session will walk you through how to use RapidMiner and Text Mining on customer service call transcripts.
Using Machine Learning to Support Physical Asset Management
This session presents a case study demonstrating a risk-based investment decision-making approach supported by machine learning for water distribution system assets.
Using Machine Learning to Detect Fraud Patterns, Anomalies, and Unusual Behaviors
This presentation shows how to leverage machine learning to detect and prevent fraud and make fraud fighters more efficient and effective.
Turn Your Employees into Sentiment-Extracting AI
This presentation covers how to use sentiment analysis to extract value from context-laden text in a fast, reliable, and objective manner.
Rewriting the Rules of Process Improvement
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.
Recommender Systems: Complex Solutions Made Simple
Master Loyalty Group presents how they created a recommendation system within RapidMiner and the benefits they have seen from doing so.
Insights Driving Actions: How to Get Real Results from Your Data Science Program
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.
Improve Your Business Insights by Building an Anomaly Detection System
This presentation discusses Verizon’s Outlier detection system, which uncovers anomalies and then allows for a deep-dive into actionable insights.
High Volume, High Frequency, Low Latency Data Processing
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.
From Prototype to Operative Software – Data Analytics at Lufthansa
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.
Fighting Sepsis with Machine Learning
VigiLanz has adopted RapidMiner to integrate machine learning and advanced analytics into its top-ranked clinical decision support suite to detect sepsis early.
Environmental Research with RapidMiner: A Case of Success
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.
Enhancing Demand Forecast through Advanced Analytics
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.
Deep Learning
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.
Clearing the Fog around Data Science and Machine Learning
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.
Accomplishing Early Prediction of LTV
Jeff Dwyer from ezCater discusses how they use RapidMiner to detect the lifetime value of a customer early on in this presentation.
AI for Lending
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.
The Right Solution for Predicting Machine Failure with RapidMiner and MapR
Learn how to predict machine failure with RapidMiner and MapR.
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.
Get Started with RapidMiner and Machine Learning
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.
ROC Curves & Lift Charts
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.
Model Selection Framework
“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.
Long Runtimes for Machine Learning Algorithms
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.
Black Boxes in Machine Learning
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.
Machine Learning for Facial Recognition
Here’s a quick video on how facial recognition works with machine learning.
Eliminating the Hidden Black Boxes in Machine Learning Models
Read the Transcript 00:00 Good morning, I hope I can still say good morning. Good morning everybody, welcome to this presentation on the elimination of
Increasing Operational Profitability through Better Flight Arrival Time Predictions
Learn how Lufthansa increased the accuracy of their flight arrival time predictions using RapidMiner, saving significant costs associated with delays.
Improving Customer Support in Electronics Manufacturing
Learn how this manufacturer uses insights from RapidMiner to adjust its operations to reduce customer support costs and improve its customer experience.
Transport for London Uses RapidMiner to Aid the Performance of the Road Network for Everyone
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.
US State Auditor Deploys Machine Learning to Tackle Healthcare Fraud
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.
Product Quality Prediction and Optimization in Steel Manufacturing
Learn how the project partners identify huge potential for the application of machine learning to predict product defects early in the production line.
Assembly Time & Plan Prediction for New 3D Product Designs
Learn how Daimler and Miele used RapidMiner to accelerate the product design and assembly planning phases in their factories to reduce time and cost.
Improving Customer Service with Text Mining and Auto-classification
Learn how LIAT uses RapidMiner to improve the time it takes to respond to customer issues and improve customer sentiment.
Big Data for Operator Support in Chemical Plants
Learn how implementing data analytics in chemical plants can prevent rare events that can lead to the loss of property and potentially life.
Reducing Risk and Improving Operational Performance in Gas Distribution
Learn how a LDC in the natural gas industry predicts which parts of its pipeline are at the greatest risk of failure with RapidMiner.
Optimizing Water Pipeline Renewal
Learn how a water distribution company leverages the insights from RapidMiner to decide where to invest in pipeline rehabilitation & replacement.
Faster AI Deployment on Hadoop and Spark with RapidMiner and Microsoft Azure HDInsight
Learn how your organization can deliver data science and machine learning on Hadoop faster than ever before with RapidMiner and Microsoft Azure and HDInsights.
How Data Science Will Play a Pivotal Role in the Future of Equipment Maintenance with RapidMiner and MapR
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.
Analyzing Customer Reviews with MonkeyLearn and RapidMiner
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.
ezCater Accomplishes Early Prediction of LTV with Stitch and RapidMiner
Jeff Dwyer from ezCater demonstrates how they use Stitch and RapidMiner to make early predictions on LTV – customer lifetime value.
How EY is Disrupting Legal, Risk, and Compliance Management with Data Science
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.
Using REST APIs and Text Mining Tools with Online Chat
Working with REST APIs can be cumbersome and challenging, in this webinar we demonstrate how to enrich and analyze chat conversations in RapidMiner Studio.
Maximizing Lead Conversion Success Using Predictive Marketing Analytics
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.
Operationalizing Artificial Intelligence with RapidMiner and Talend
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.
Putting your Analytics into Action with FICO
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.
Elaborate your Time Series Analysis with RapidMiner
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
Intuitive Data Prep for Machine Learning
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.
Automatic Feature Engineering with RapidMiner Auto Model
RapidMiner Founder Dr. Ingo Mierswa outlines how RapidMiner incorporates a novel approach for automatic feature engineering with RapidMiner Auto Model.
Introducing 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.
4 Real-Time Scoring Use Cases
Read through this ebook to learn more about Real-Time Scoring use cases for high volume, low latency, and upsell opportunities.
Better Machine Learning Models with Multi-Objective Optimization
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.
Data Science: Concepts and Practice (Second Edition)
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.
The Issue of Deploying Models in Production
In this article, we cover common issues we encounter when deploying ML models and how the combination of Talend and RapidMiner help overcome them.
6 Ways Machine Learning is Revolutionizing Manufacturing
Machine learning is constantly making every stage of manufacturing more efficient and lucrative. Learn how to harness its power for your business.
Scoring Data with RapidMiner Auto Model and Zapier
Learn how to connect RapidMiner Auto Model with other applications through Zapier, which has connectors to nearly every application that exists.
Artificial Intelligence
Artificial intelligence is changing our world in more ways than we can see or even imagine. But there’s a lot of fiction about the fact of AI. This article explains everything you need to know about AI, what it really does and why it matters.
Data Science
Data science is helping us change our world in ways we never even knew. Do you know how it works and why it’s important? Read this article to find out.
Data Preparation
Are you wondering what relevance data preparation has to your company or organization? Here’s what you don’t know about data prep and how it can help you.
Automated Machine Learning
Automated machine learning holds the key to democratizing data science. Learn how to gain valuable insights that will drive innovation with Auto ML.
Data Science: Concepts and Practice (Second Edition) now available
Data Science: Concepts and Practice (Second Edition) by Vijau Kotu and Bala Deshpande is now available. Order your copy today.
Risk Management
Modern risk management demands the latest data science technology. Learn the opportunities and challenges involved in optimizing your business.
Machine Learning
Are you wondering what machine learning (ML) is and how it can help your business? This article tells you all about it and how it works.
Predictive Marketing Analytics for the Entire Customer Journey
Learn how predictive marketing analytics can help engage your audience in all the different stages of a customer journey and maximize lead conversion.
How Machine Learning, Big Data & AI are Changing Energy
Learn how artificial intelligence (AI), machine learning (ML), and big data are changing the renewable energy sector by taking advantage of collected data.
Make better product decisions with MonkeyLearn and RapidMiner
Learn how to structure and analyze customer reviews by sentiment and topic with machine learning and natural language processing.
Machine Learning On Hadoop
Learn about the importance of Hadoop and how you can use it to give your business a competitive advantage.
Advanced Analytics vs Business Intelligence
Learn the difference between traditional business intelligence (BI) and the modern approach of advanced analytics.
RapidMiner Wisdom 18 Recap – Day Two
Here’s a recap of the presentations from the second day of Wisdom 2018 in New Orleans. Wisdom is RapidMiner’s conference for users.
RapidMiner Wisdom 18 Recap – Day One
Here’s a recap of the presentations from the first day of Wisdom 2018 in New Orleans. Wisdom is RapidMiner’s conference for users.
Data Preparation: Time consuming and tedious?
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.
3 ways to ruin your business with data science
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.
10 reasons why you need to upgrade to RapidMiner 9 today!
RapidMiner regularly releases new versions of RapidMiner Studio, Server and Radoop. Read the top 10 reasons to upgrade to RapidMiner 9.
Data prep and machine learning made fun, fast and simple
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.
Scaling Data Science Without Data Scientists
Check out these data science case studies produced by undergraduate students using RapidMiner in an annual data science competition.
Doc Ingo, what model should I use?
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.
Introducing RapidMiner Real-Time Scoring
RapidMiner’s Real-Time Scoring Agent extends Server with a lightweight execution engine designed for specific use cases where speed and volume are critical.
Announcing a Free Trial for Everyone
Today RapidMiner announced that we’re giving everyone a 30-day trial of Studio Large. Everyone will automatically receive the 30-day trial license.
Enterprise Data Science, faster and more secure with RapidMiner 8.1
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.
Accelerated Modeling without the Black Box
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.
Better Machine Learning Models With Multi-Objective Feature Selection: Part 4
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.
Better Machine Learning Models with Multi-Objective Optimization
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 for Feature Selection: Part 3
Multi-objective optimization is great for feature selection because we can find all potentially good solutions without defining a trade-off factor.
Evolutionary Algorithms for Feature Selection: Part 2
Evolutionary algorithm is a generic optimization technique mimicking the ideas of natural evolution with the concepts of crossover, mutation, and selection.
Better Machine Learning Models with Multi-Objective Feature Selection: Part 1
Feature selection can greatly improve your machine learning models. Learn about it’s importance in part 1 of this blog series.
Selling Data Science: Unboxing the Black Box
Data Scientist Vladimir Mikhnovich discusses how to overcome the challenges that come with selling data science to your internal stakeholders.
Minimizing Machine Failure with RapidMiner and Tableau
Remove obstacles to developing useful machine learning outputs and how to gain insights with the integration of RapidMiner and Tableau.
RapidMiner 8.0: Containerized Server Architecture and UI
RapidMiner 8.0 will bring new features that offer improved reliability and horizontal scalability, to which we will expand the platform and revamp Server.
Better Together – Minimizing Machine Failure with RapidMiner and Tableau
Learn how RapidMiner and Tableau provide a complete solution for analytics teams. See how these two platforms can be applied in manufacturing.
Ten Tips to Master RapidMiner Studio
We’ve compiled the top ten most useful tips and tricks from our data science team to help you master our RapidMiner Studio.
An Introduction to Deep Learning with RapidMiner
Learn the basics of deep learning with Philipp Schlunder, Data Scientist at RapidMiner. He covers the main components used in creating neural networks.
Code Free Data Science on Hadoop
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.
Enhance your Call Center Operations with RapidMiner
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
How to Ruin Your Business with Data Science and Machine Learning
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.
Naïve Bayes – Not so naïve after all!
Naïve Bayes is a powerful machine learning technique. Learn more about this classifier below and make it part of your standard toolbox.
Discover New Machine Learning Use Cases for Hadoop with RapidMiner SparkRM
This webinar shows you real world use cases for machine learning on Hadoop using RapidMiner’s new SparkRM capabilities.
What Artificial Intelligence and Machine Learning can do – and what not
What exactly are we doing with AI? Learn about what artificial intelligence and machine learning can do – and what it can’t do.
From the Rosette API Academic Program: Tweet Sentiment and Brazilian Politics
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: A Simple Machine Learning Algorithm
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.
Embed Predictive Analytics into your Applications with RapidMiner
Learn how modern predictive analytics helps manage and accelerate all phases of the predictive analytic process lifecycle, from source to result.
What is Data Science?
What is data science? Have you read about the relationship between AI, machine learning, and deep learning? How do they relate to data science ?
What is Artificial Intelligence, Machine Learning, and Deep Learning?
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.
Time Series Forecasting with RapidMiner and R
Learn more about time series forecasting in RapidMiner Studio and with R. R integrates well within RapidMiner in order to handle time series forecasting.
Process Mining with RapidMiner
Learn how to do process mining with RapidMiner, covering concepts such as process discovery, process conformance analysis, and process performance analysis.
Building a Sales Forecasting Solution with RapidMiner
Learn how to build a Sales Pipeline Analysis solution using RapidMiner, removing the bias that plagues traditional forecasting processes.
Reading the Tea Leaves of Recent Data Science Analyst reports
RapidMiner is a leader in both the Gartner’s Magic Quadrant for Data Science and the Forrester Wave: Predictive Analytics and Machine Learning Solutions.
How to Correctly Validate Machine Learning Models
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.