29 Apr 2019admin

Author: David Kolb

A lot of people associate the word “development” and KNIME Analytics Platform with creating workflows with nodes. But what exactly is a node and where do nodes come from?

A node is the smallest programming unit in KNIME. Each node serves a dedicated task, from very simple tasks - like changing the name of a column in a table - to very complex tasks - such as training a machine learning model. A node is contained in an extension. One of the jobs a developer does at KNIME is create new extensions or nodes for existing extensions. However, as openness is very important for us at KNIME, everyone can contribute to our platform.

KNIME Extensions
Fig. 1 The diagram shows the different types of extensions and integrations within KNIME Analytics Platform.

There are lots of ways to extend KNIME, but node development, i.e. writing extensions, to add the specific functionality you or your company needs, is probably the most common.

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15 Apr 2019heather.fyson

Authors: Maarit Widmann, Anna Martin, Rosaria Silipo

Do you remember the Iron Chef battles?

It was a televised series of cook-offs in which famous chefs rolled up their sleeves to compete in making the perfect dish. Based on a set theme, this involved using all their experience, creativity, and imagination to transform sometimes questionable ingredients into the ultimate meal.

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08 Apr 2019admin

Authors: Paolo Tamagnini, Simon Schmid, and Christian Dietz

Is it possible to fully automate the data science lifecycle? Is it possible to automatically build a machine learning model from a set of data?

Indeed, in recent months, many tools have appeared that claim to automate all or parts of the data science process. How do they work? Could you build one yourself? If you adopt one of these tools, how much work would be necessary to adapt it to your own problem and your own set of data?

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01 Apr 2019admin

Author: Casiana Rimbu

In March 2019, we hosted the KNIME Spring Summit for the twelfth time. It brought together KNIME users from all over the world. If you weren't able to make it to Berlin this year, watch the live video recordings from the summit, below, to learn about what’s new in KNIME Analytics Platform and KNIME Server.

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25 Mar 2019admin

Author: Rosaria Silipo

LSTM recurrent neural networks can be trained to generate free text.
Let’s see how well AI can imitate the Bard.

“Many a true word hath been spoken in jest.”
― William Shakespeare, King Lear

“O, beware, my lord, of jealousy;
It is the green-ey’d monster, which doth mock
The meat it feeds on.”
― William Shakespeare, Othello

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18 Mar 2019admin

Authors: Rosaria Silipo and Kathrin Melcher

The key to perform any text mining operation, such as topic detection or sentiment analysis, is to transform words into numbers, sequences of words into sequences of numbers. Once we have numbers, we are back in the well-known game of data analytics, where machine learning algorithms can help us with classifying and clustering.

We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.

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11 Mar 2019admin

Author: Ted Hartnell (CTO of Scientific Strategy)

What is Market Simulation?

A market simulation is a way to model a real world market. Just as real world markets have products, features, brands, stores, locations, and competitive rivals, so does a market simulation. But what makes a market simulation truly realistic are the customers. Simulations can generate tens of thousands of virtual customers designed to mimic the purchase decisions of real world shoppers. Customers evaluate the differentiation offered by each product.

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04 Mar 2019admin

Authors: Maarit Widmann & Casiana Rimbu

How to build a pivot table in KNIME Analytics Platform

To pivot or not to pivot, that is the question.

Did you know that a pivot table allows you to quickly summarize your data based on a group, pivot, and aggregation columns? This summary might include sums, averages, or other statistics, which the pivot table splits the statistics is a meaningful way for different subgroups and draws attention to useful information.

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25 Feb 2019admin

Authors: Jakob Schröter & Marc Bux (KNIME)

Have you ever wondered how far you could push the boundaries of workflow design? Did you ever want to give free rein to your imagination when creating views in KNIME Analytics Platform? Do you also fancy the occasional round of cards? If the answer to either of these questions is “yes”, then this blog post is for you. Today, we’re creating our own game of blackjack in KNIME. We do this by using the Tile View (JavaScript) and CSS Editor nodes as well as the revised visual layout editor introduced in the latest KNIME release.

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18 Feb 2019admin

Authors: Giuseppe Di Fatta (University of Reading, UK) and Stefan Helfrich (KNIME)

Are you an expert in KNIME Analytics Platform? There is now an official way to answer this question and share it with the world: You can test your KNIME proficiency with a new certification program developed by a collaboration between academia and industry.

Professional certifications are particularly useful in the employment process to help identify key skills relevant to the job profile sought by employers. They facilitate matching the demand for skills with the offer at an earlier stage and also promote the need for the right skills. They help prospective applicants to understand the requirements in the current job market to plan their training and development more effectively. Employers can also use certifications to engage current employees in Continuous Professional Development (CDP) relevant to critical needs. While Higher Education degrees are evidence of a solid knowledge of a subject area (e.g., BSc Computer Science, MSc Data Science), certification programs tend to focus on very specific expertise and skills on industry-relevant tools and processes. Certification programs can help to ensure the right competence level is clearly identified and communicated. Certification tests are used to assess skills and knowledge for this purpose.

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