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How to Think about Bias in Machine Learning

Learn what bias is in the world of machine learning. We’ll look at three main things someone might mean when they refer to a biased model—real-world bias, sampling bias, and model bias.

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A New Era of Automation in Manufacturing

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.

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A Beginner’s Guide to Machine Learning

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.

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A Beginner’s Guide to Data Science

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. 

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10 Key Takeaways from the DATAcated Conference 2021

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.

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Announcing Plant-Based Machine Learning

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!

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3 Biggest Tech Trends Driving the Automotive Industry in 2021

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.

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Top 5 IIoT Implementations in Manufacturing

Industrial Internet of Things (IIoT) is already transforming manufacturing operations across the globe through several common implementations. Let’s look at some examples.

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Data Science Automation: A Complete Guide

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.

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Using Machine Learning for Predictive Maintenance

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.

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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.

White semi trucks
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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.

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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.

A helping hand
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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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 ?

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Cross Validation: Why & How to Do It

Learn how k-fold cross-validation is the go-to method whenever you want to validate the future accuracy of a predictive model.

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Why You Should Ignore the Training Error

Training errors can be dangerously misleading. Discover which practices will provide you with better estimation techniques for your model.

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The Data Core Project

We kicked-off a special-purpose project, named the Data Core Project, to revise the core data management and processing core of RapidMiner.

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Start a Data Science Project in Minutes

Start a Data Science Project with RapidMiner’s Data Science Expert Marketplace; helping you close the data science skills gap.

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Unlock Behavioral Insight from MongoDB

Learn how to use data from MongoDB in RapidMiner to help website owners measure the successes of their online business goals.

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How to Join Your Data [Tips + Tricks]

How to join data in RapidMiner. 7 easy ways to mash up your data in SQL fashion without writing SQL and using RapidMiner instead.

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Tips & Tricks: Get Wisdom of Crowds

Similar to Amazon recommendations, RapidMiner shows you which operator other data scientists would use next if they were building your process.

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The RapidMiner Philosophy

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.” 

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Wisdom of Crowds: The Guiding Light

There are more than 250,000 RapidMiner users worldwide, brilliant minds who have had tasks similar to yours – building some analytical process.

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RapidMiner Acquires Radoop

Radoop, a leading big data analytics solution, makes Hadoop implementations more powerful and easy to use with RapidMiner’s advanced analytics suite.

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Thanks RapidMiner Community…

We believe that our placement in the Leaders quadrant reflects our status as one of the world’s most frequently downloaded predictive analytics tools.

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The core of RapidMiner is open source

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. 

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Books on Data Mining

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.

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New Plotters for RapidMiner

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.

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Regular Expression Madness

I just stumbled upon this great blog post about some uncommon uses of regular expressions. RapidMiner also makes a lot use of those beasts.

Extended Operations for Nominal Values
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Extended Operations for Nominal Values

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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