A new book by Packt Publishing

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A few days ago, at the KNIME Fall Summit, I announced the new book “Codeless Deep learning with KNIME”, which I co-authored with my colleague Kathrin Melcher and is soon to be published by Packt Publishing.

Now, in the post Fall Summit relaxation, and talking to myself in these times of COVID induced isolation, I was wondering why we invested all this time writing this book and why people should read it. I will report here this short conversation I had with myself.

Q. Do we really need one more book about deep learning?

A. Indeed, there are plenty of…


Do not worry, but worry

Interviewer: Paolo Tamagnini, KNIME

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From the left: Rosaria Silipo, Paolo Tamagnini, and Diego Arenas. (Pictures from interviewer and interviewees)

Some time ago, after his/her keynote talk at an important conference, a colleague of mine, made the statement that nowadays, every presentation about artificial intelligence (AI) [and related challenges for the future] need to be at least apocalyptic. It is true. By now, most documentaries, shows, TED talks, keynotes, and similar presentations clearly use a very technophobic tone. How much of this is true?

Are we really doomed and should we just surrender to AI?

Is AI going to take over humanity?

Is AI black magic?

Is it true that once you set an AI application…


Find the Right Metric for a Prediction Model

By Maarit Widmann, Data Scientist, KNIME

Quantitative data have endless stories to tell!

Daily closing prices tell us about the dynamics of the stock market, small smart meters about the energy consumption of households, smartwatches about what’s going on in the human body during an exercise, and surveys about some people’s self-estimation of a topic at some point in time. Different types of experts can tell these stories: financial analysts, data scientists, sports scientists, sociologists, psychologists and so on. Their stories are based on models, for example, regression models, time series models and ANOVA models.

Why Are Numeric Scoring Metrics…


An interview on exploring techniques and use cases for text mining

Author: Rosaria Silipo

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Surfing the web for blog posts and journal articles about KNIME software and data science

Author: Rosaria Silipo

If you want to learn more about KNIME Analytics Platform, you can of course explore the KNIME Web site. There you can find a whole LEARNING page, including links to in-house courses, external courses, certification exams, and YouTube videos. In addition to those, you can find more resources out there on the web, provided by the KNIME community.

It is the end of the year: time for summaries and rankings. Here is my very personal list of the top 10 most interesting blog posts about KNIME software, published in 2020 by the KNIME community. As you all…


A Review of Text Mining Use Cases

Author: Rosaria Silipo

Text mining is a very rich branch of data science, filled with extremely useful techniques. It allows us to understand the topic of a conversation and, therefore, to summarize it; to quantify the sentiment of the speakers and to reply in the most appropriate tone; to recognize entities hidden in texts; even to generate free texts and automatic answers. All of that is possible with just a few nodes with the Text Processing extension within KNIME Analytics Platform.

In the Evangelism group at KNIME, we have worked for years on text mining applications. Now the moment has…


Find the Right Metric for a Prediction Model

by Maarit Widmann

Quantitative data have endless stories to tell!

Daily closing prices tell us about the dynamics of the stock market, small smart meters about the energy consumption of households, smartwatches about what’s going on in the human body during an exercise, and surveys about some people’s opinion of a topic at some point in time. Different types of experts can tell these stories: financial analysts, data scientists, sports scientists, sociologists, psychologists, and so on. Their stories are based on models, for example, regression models, time series models and ANOVA models.

Why Are Numeric Scoring Metrics Needed?

These models have many consequences in the real…


Applying t-SNE to Visualize the MNIST Digits Dataset in 2D Plots

Authors: Rosaria Silipo and Mischa Lisovyi, KNIME

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Is zero closer to eight or to one? Is this a three or a five? This was the type of question we were pondering a few weeks ago when we examined the results of an image classification application.

Yes, indeed, a zero is closer to an eight than to a one and a two is closer to a five than to a three — of course, from an image recognition point of view rather than in a strictly mathematical sense. In the last data science example that we were preparing, we trained a…


Data Blending with KNIME — Expanded and Updated

by Lada Rudnitckaia & Rosaria Silipo

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Download the free ebook “Will They Blend? Data Blending with KNIME
  • The second edition of the “Will they blend?” e-book is hot off the press and free to download from the KNIME Press page.
  • It now contains 32 chapters describing data blending for more than 50 data sources and external tools, from classic and new databases to cloud resources, from Sharepoint and SAP to web services and social media.

Data Blending is a Challenge … Or Is It?

Data often reside on different dislocated data sources: on your machine, in the cloud, in a remote database, on a web service, on social media…


An alternative for when overall accuracy is biased, yet not trusting the statistics blindly

by Maarit Widmann

Introduction

Cohen’s kappa is a metric often used to assess the agreement between two raters. It can also be used to assess the performance of a classification model.

For example, if we had two bankers, and we asked both to classify 100 customers in two classes for credit rating, i.e. good and bad, based on their creditworthiness, we could then measure the level of their agreement through Cohen’s kappa.

Similarly, in the context of a classification model, we could use Cohen’s kappa to compare the machine learning model predictions with the manually established credit ratings.

Like many other…

Rosaria Silipo

Rosaria has been mining data since her master degree, through her doctorate and job positions after that . She is now a data scientist and KNIME evangelist.

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