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Articles by Roberto Cadili
KNIME Game of Nodes, Season 2- It’s Here!
GETTING STARTED | DATA LITERACY | KNIME ANALYTICS PLATFORM Learn more about KNIME’s data science world tournament and how to take part Roberto Cadili · Follow Published in Low Code for Data Science · 3 min read · -- Hark! I summon thee to a contest of nodes. Art thou endowed with the courage for the encounter?
An introduction to the Naive Bayes classifier and how to use it
DATA SCIENCE THEORY | MACHINE LEARNING | KNIME ANALYTICS PLATFORM A theoretical explanation and an implementation using KNIME’s visual workflows Roberto Cadili · Follow Published in Low Code for Data Science · 6 min read · -- Photo by Hunter Harritt on Unsplash. About the author: Alberto Montanari has a degree in Mechanical Engineering and spent his career with the Fiat Chrysler Automobiles Group as President of many companies around the world.
Alteryx to KNIME Migration FAQs
Choosing new data tools can be a daunting exercise for any team. But executives must stay vigilant to select the platforms that deliver positive ROI and align with their organization’s goals and priorities. Here we answer some of your most commonly asked questions when migrating from Alteryx to KNIME. Onboarding and Ease of Use It’s both.
What’s New in KNIME Analytics Platform 5.3
KNIME’s goal is to build an open source platform that makes working with the latest advancements in data and AI possible for everyone. With the release of KNIME Analytics Platform 5.3, we continue to strengthen our commitment to the community by delivering many user-requested features — a new workflow monitor for easier debugging, a revised Home tab for faster navigation, a new Expression node to work with text and numbers in a manner akin to spreadsheet formulas, and much more.
The 9 steps to a successful Data Connect event
Here we summarize how to make a Data Connect happen, what kind of support you can expect from us, here at KNIME, plus some notes on the application form to host the event. Identifying the speakers and their topics is the key point of every Data Connect event. Typically, a Data Connect will invite two speakers to talk on a related theme. You can get inspiration for topics from previous events. Maybe you want to speak, yourself, or you have friends or colleagues with a data science project to share.
Of open-source LLMs and ever-green ML principles
Our fortnightly selection of must-reads from the community, for the community As data scientists in the age of AI, it's imperative to keep our knowledge and skills up-to-date. Especially now that open-source technology and models are flourishing and are becoming increasingly easier to access. With the rapid growth of open-source models, the gap between open-source and closed-source solutions is narrowing significantly too.
KNIME Spring Summit 2024, April 15-17 - Save your spot! ⭐
EDITOR’S PICK | KNIME SUMMIT | KNIME ANALYTICS PLATFORM Join us onsite in Austin, Texas to enjoy all the activities or get your free virtual pass to access the live stream Join your peers for KNIME Spring Summit 2024 on April 15–17. Taking place in Austin, Texas, this is a three-day conference on topics related to building and scaling the adoption of data analytics, data science, GenAI, and machine learning solutions — all using KNIME Software.
Take the 90-day data science certification challenge
GETTING STARTED | CERTIFICATIONS | KNIME ANALYTICS PLATFORM Get your data science expertise certified for free About the author: Schalk Gerber is Education Manager on the Evangelism team at KNIME. As a certified instructional designer, he is involved in various aspects of course design, content creation, and certification.
Write with a Content Writing Template
CONTRIBUTE | CONTENT WRITING | KNIME ANALYTICS PLATFORM Streamline the creation of data stories and showcase your KNIME solutions in under 1 hour🚀 KNIME owes a large part of its success to the contributions from the community. Although many community members develop excellent analytical solutions, the challenges of everyday life often hinder them from finding time to write about their workflows for others to learn from.
The art of simplicity in predictive analytics
The art of simplicity in predictive analytics Do we always really need to implement highly complex systems that require long training time and large datasets to obtain accurate predictions? As data scientists, we are prone to (mistakenly) assume that the “more articulated” or “deeper” (in the case of neural architectures) the models, the better the results will be.
A Low-Code Solution for Early Diabetes Prediction
Rosaria: Let's introduce our guests, hear about the results of their projects and their learning journeys. Can you tell us more about yourselves and your study program? Luca: I'm a 22-year-old data science student. I've been passionate about scientific subjects, especially computer science since high school. During my university studies at the University of Milano-Bicocca, I focused on statistics, aligning my career around the realm of data that captivates me.
Machine Learning for All
Our fortnightly selection of must-reads from the community, for the community The Oxford English Dictionary defines machine learning as "a type of artificial intelligence in which computers use huge amounts of data to learn how to do tasks rather than being programmed to do them". While accurate, this definition doesn't give us a good understanding of how all-pervasive machine learning-driven technology is in our everyday life.
Findings from the Data Science for Business Challenge at TH Köln
Roberto: For this episode, my co-interviewer is Stefan: Sure! I am responsible for the Roberto: Let's now introduce our guests, get insights into the analysis they conducted, the tools and methodologies used and what they learned throughout this challenge. We hope that other students and aspiring data professionals will find some source of inspiration and motivation in your story. Stefan: Welcome Prof. Tobias Schlüter; Margarethe, Julia, Hanna from Team 1; and Markus from Team 2.
Brand Reputation Measurement using Social Media
DATA STORIES | BRAND REPUTATION | KNIME ANALYTICS PLATFORM This famous quote, attributed to Jeff Bezos, Amazon's founder, is one of our favorites. It is not without criticism, but it is an apt way to approach the measurement of branding. Building a brand is on every marketer's task description. But how do you do it? And foremost: How do you measure what you have built (and hopefully are still building)?
To code or not to code? That is no longer the question
Our fortnightly selection of must-reads from the community, for the community In large organizations, data teams use various sets of tools or coding platforms to perform their tasks. The productivity of the data team is higher if everyone can collaborate and work while still using their preferred tool. Imagine an organization where some data teams perform their tasks with a visual programming-based tool while others are using Python, JavaScript, Java or R.
Meet your local low code community
GETTING STARTED | DATA SCIENCE COMMUNITY | KNIME ANALYTICS PLATFORM The idea that data geeks are shy, introverted, Sheldon Cooper-like characters who know it all, and prefer the company of their PCs is mostly a Hollywood invention. The truth is that the complexity of the modern data science life cycle requires the experience and expertise of several data professionals.
Book Metadata and Cover Retrieval Using OCR and Google Books API
By Roberto Cadili, Data Scientist, KNIME & Lada Rudnitckaia, Data Scientist, KNIME Figure 1: Examples of book edition notices where information can be extracted thanks to OCR. Most of the time, the raw data that we need for our data science project is not organized in a neat, well-structured, and insightful table. Rather, this is sometimes stored as text in a scanned document. Words in the document must then be extracted one by one to form a text formatted data cell.
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