AI in action: reshaping data science — Part II
Our fortnightly selection of must-reads from the community, for the community
GenAI has dramatically transformed data science, reshaping the roles, processes and opportunities of data scientists and organizations alike. Its advanced algorithms and computational capabilities have empowered data scientists to tackle challenges that were once considered insurmountable, pushing the boundaries of what can be achieved with data-driven insights. This paradigm shift has not only accelerated the pace of innovation but has also democratized access to data science tools, allowing individuals from diverse backgrounds to participate in the creation of cutting-edge solutions. As a result, the field of data science has become more dynamic and inclusive, with opportunities for collaboration and discovery abound.
The articles that we selected for this edition of the Workflow focus again on KNIME and its AI capabilities for data science. From a compelling example to adopt the GenAI Canvas for personalized financial planning in the banking sector, to a brilliant tutorial to create AI agents using the CrewAI framework in KNIME, don’t miss out on this great content. The last story collects insights from a seasoned data scientist who ventures into some ‘philosophical’ aspects about how and why ML and AI projects may fail or succeed. Happy reading!
KNIME Spring Summit 2024, April 15–17 — Save your spot! ⭐
Join us onsite in Austin, Texas to enjoy all the activities or get your free virtual pass to access the live stream.
Building a Personalized Financial Planning Assistant with Generative AI
By Ali Alkan
The Generative AI Canvas offers a powerful tool for brainstorming and developing innovative applications of generative AI across various industries. In his follow-up article, Ali Alkan shares an insightful tutorial where it shows step-by-step how to use the KNIME “GenAI Canvas for Enterprises” component he developed. He shows how the GenAI Canas component can be adapted for personalized financial planning in the banking sector, outlining benefits and challenges. Check it out!
Integrating Agent Frameworks into Low Code Tools: Making CrewAI work in KNIME
AI agents represent a cutting-edge advancement in GenAI. These agents leverage sophisticated algorithms, including natural language processing and machine learning, to understand user queries and generate content. By mimicking human conversation patterns and understanding context, these agents can provide personalized responses, recommendations, and assistance across various domains. In this article, Martin Dieste shares an insightful tutorial on how to integrate Crew AI, a Python-based AI agent framework, into a low-code tool like KNIME for the creation of a blog post writer agent. He explains how to define agents, tasks, and set up the proper Conda environment to expose it in the KNIME workflow. Don’t miss it out!
About Machine Learning — How it Fails and Succeeds
The power of machine learning lies in its ability to uncover patterns, make predictions, and derive insights from vast datasets that would overwhelm human capabilities. In this article, Markus Lauber shares a collection of insights from his long-term experience practicing data science, venturing into some more ‘philosophical’ aspects about how and why ML and AI projects may fail or succeed. He explains why CRISP-DM is still relevant today, encourages thinking about the business problem before starting any data modeling, emphasizes the importance of data preparation, and much more. All along, he provides links to working examples with KNIME for those who would like to explore the hands-on side of things.
We love learning new creative solutions using KNIME from the articles that we publish, and we love to share them with you. We are proud of building together a thriving community that supports each other, shares experiences, and shapes the future of low code data science.
See you in the next Workflow,
The Editors of Low Code for Data Science
PS: 📅 #HELPLINE. Want to discuss your article? Need help structuring your story? Make a date with the editors via Calendly (every second Thursday).
