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RapidMiner Blog

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Announcing RapidMiner’s SOC 2 Security Certification

We’ve made it a priority to be compliant with the highest standards for securing enterprise data so that our customers can build impactful solutions without introducing unnecessary risk. Learn more.

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ML Engineer vs. Data Scientist: What’s the Difference?

While both machine learning engineers and data scientists are hands-on roles, their skills and day-to-day looks vastly different from one another. In this post, we’ll break down the difference.

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5 Powerful Use Cases of AI in Manufacturing

Artificial intelligence helps all kinds of manufacturers work quicker and smarter. Here are some of the most impactful use cases of AI in manufacturing.

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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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Cluster Analysis: Everything You Need to Know

Whether you’re a plant manager focused on minimizing product defects or a marketer who wants to predict the results of an upcoming campaign, there’s a

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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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探索的模型去模拟使用房价Data

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.

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4 Data Modeling Techniques to Drive Business Impact

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.

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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.

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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.

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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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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.

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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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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.

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3 ways to ruin your business with data science

机器学习和数据科学已经成为我乐鱼平台进入ntrinsic part of business. Learn how to avoid common data science mistakes that can ruin your business.

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Scaling Data Science Without Data Scientists

看看这些数据科学的情况乐鱼平台进入studies produced by undergraduate students using RapidMiner in an annual data science competition.

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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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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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加速模型没有黑色的盒子

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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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.

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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 ?

Time Series
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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.

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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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RapidMiner’s New Parallel Cross-Validation

Now that we have ported the cross-validation operator to make use of parallel execution, you can ultimately produce better results, faster.

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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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使用机器学习来驱动客户保留

Use Machine Learning to understand complex customer behavior patterns. Use RapidMiner to extract those relationships and drive customer retention quickly.