A Coding Guide to Build a Functional Data Analysis Workflow Using Lilac for Transforming, Filtering, and Exporting Structured Insights

A Coding Guide to Build a Functional Data Analysis Workflow Using Lilac for Transforming, Filtering, and Exporting Structured Insights

In this tutorial, we demonstrate a fully functional and modular data analysis pipeline using the Lilac library, without relying on signal processing. It combines Lilac’s dataset management capabilities with Python’s functional programming paradigm to create a clean, extensible workflow. From setting up a project and generating realistic sample data to extracting insights and exporting filtered…

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How AI Agents Are Transforming the Education Sector: A Look at Kira Learning and Beyond

How AI Agents Are Transforming the Education Sector: A Look at Kira Learning and Beyond

Today’s classrooms are changing fast because of Artificial Intelligence (AI). AI agents are now part of how teaching and learning happen. They do more than automate tasks. These agents help teachers provide personal support and give students feedback that fits their own learning style. Kira Learning is a platform leading this change. It uses AI…

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AI-Driven Customer Experience: Transforming Business Models

AI-Driven Customer Experience: Transforming Business Models

In the rapidly evolving landscape of modern business, Artificial Intelligence (AI) is not just a buzzword—it’s a transformative force reshaping the very foundations of customer experience. As businesses strive to meet the ever-increasing expectations of their clientele, AI emerges as a game-changing ally, enabling personalization at an unprecedented scale and unlocking new frontiers in customer…

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Reinforcement Learning Meets Chain-of-Thought: Transforming LLMs into Autonomous Reasoning Agents

Reinforcement Learning Meets Chain-of-Thought: Transforming LLMs into Autonomous Reasoning Agents

Large Language Models (LLMs) have significantly advanced natural language processing (NLP), excelling at text generation, translation, and summarization tasks. However, their ability to engage in logical reasoning remains a challenge. Traditional LLMs, designed to predict the next word, rely on statistical pattern recognition rather than structured reasoning. This limits their ability to solve complex problems…

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