A new book by Packt Publishing

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…


Author: Rosaria Silipo

Image produced and authorized by KNIME

I get, often, questions like these from young aspiring data scientists: “What do I need to become a data scientist? Is the three-month course I am taking on Coursera enough? Do I need to learn how to code? Do I need to learn Python? How many years of hands-on experience do I need?” And many other similar questions.

Data Science has emerged in the last few years as one of the most in demand skills. Data Scientists are sought after and often paid well enough. Obviously, the interest has also increased. What does it take to become…


Exploring the Wonders of the GroupBy Node for Statistical Aggregations

Author: Roberto Cadili

Note. This blog post has been separated in two parts. This is Part II. “Aggregations, Aggregations, Aggregations! — Part I” has been published on Analytics Vidhya on March 19, 2021.

Figure 1. The GroupBy node in KNIME Analytics Platform

Better Data Summary with Statistical Aggregations

Welcome back to our conversation on data aggregation using the GroupBy node. In the last blog post “Aggregations, Aggregations, Aggregations! — Part I”, we have shown how to aggregate data by using basic aggregation operations such as “Count” and “Sum”.


Exploring the Wonders of the GroupBy Node for basic aggregations

Author: Roberto Cadili

This blog post has been separated in two parts. This is Part I. Part II to follow in the next few days.

Fig. 1. The GroupBy node in KNIME Analytics Platform

Always in need of aggregations

There are many levels to look at data. Sometimes, looking at just the raw data doesn’t bring out the information we need. Often the operation required to move from one level to the next is aggregation.

Let’s take a dataset of purchase contracts as an example. The pure list of contracts (the raw data), though informative, does not tell us much about the customer contribution…


Do not worry, but worry

Interviewer: Paolo Tamagnini, KNIME

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


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…

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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