Intelligent
An Intelligent Conversational Machine Learning Pipeline Integrating LangChain Agents and XGBoost for Automated Data Science Workflows
In this tutorial, we combine the analytical power of XGBoost with the conversational intelligence of LangChain. We build an end-to-end pipeline that can generate synthetic datasets, train an XGBoost model, evaluate its performance, and visualize key insights, all orchestrated through modular LangChain tools. By doing this, we demonstrate how conversational AI can interact seamlessly with…
Mixed signals, on a power budget: Intelligent low-power analog in MCUs
It goes without saying that battery-powered devices are sensitive to power draw, especially during periods of inactivity. One such use case is in sensor nodes or portable sensors—these devices passively monitor a specific condition. When the threshold is exceeded, they trigger an alarm or log the event for further analysis. Since most devices incorporate some…
A Coding Guide to Build an Intelligent Conversational AI Agent with Agent Memory Using Cognee and Free Hugging Face Models
In this tutorial, we delve into building an advanced AI agent with agent memory using Cognee and Hugging Face models, utilizing entirely free, open-source tools that work seamlessly in Google Colab and other notebook. We configure Cognee for memory storage and retrieval, integrate a lightweight conversational model for generating responses, and bring it all together…
A Code Implementation for Designing Intelligent Multi-Agent Workflows with the BeeAI Framework
BeeAI FrameworkIn this tutorial, we explore the power and flexibility of the beeai-framework by building a fully functional multi-agent system from the ground up. We walk through the essential components, custom agents, tools, memory management, and event monitoring, to show how BeeAI simplifies the development of intelligent, cooperative agents. Along the way, we demonstrate how…
Build an Intelligent Multi-Tool AI Agent Interface Using Streamlit for Seamless Real-Time Interaction
In this tutorial, we’ll build a powerful and interactive Streamlit application that brings together the capabilities of LangChain, the Google Gemini API, and a suite of advanced tools to create a smart AI assistant. Using Streamlit’s intuitive interface, we’ll create a chat-based system that can search the web, fetch Wikipedia content, perform calculations, remember key…
A Coding Guide for Building a Self-Improving AI Agent Using Google’s Gemini API with Intelligent Adaptation Features
In this tutorial, we will explore how to create a sophisticated Self-Improving AI Agent using Google’s cutting-edge Gemini API. This self-improving agent demonstrates autonomous problem-solving, dynamically evaluates performance, learns from successes and failures, and iteratively enhances its capabilities through reflective analysis and self-modification. The tutorial walks through structured code implementation, detailing mechanisms for memory management,…