D&D AI Dungeon Master Tutorial Albert shows how to create an AI-powered D&D Dungeon Master using LangGraph. This tutorial combines graph-based AI agents with automated UI generation to bring your D&D games to life. Learn to build your own AI DM https://
youtu.be/amyMz1fXwoU
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Create AI-Powered D&D Dungeon Master with LangGraph Tutorial
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Smart Health Agent: GPU-Accelerated Multi-Agent System for Real-Time Monitoring
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Smart Health Agent A GPU-accelerated multi-agent system providing real-time health monitoring with personalized insights. Built with LangGraph to orchestrate agents that process health metrics and environmental data. Check it out here https://
github.com/jayrodge/ai-ag
ents/tree/main/smart_health_agent
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Production-Ready AI Agents: A Practical Guide with LangGraph
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Agents Towards Production Nir Diamant just released a practical guide for building production-ready AI agents. This open-source playbook features tutorials using LangGraph for workflows and LangSmith for observability, plus essential production features. Check it out
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Google Unifies AI Developer Tools Under AI Studio Platform
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We are trying to unify all AI Developer stuff under AI Studio
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Deleting All Errors May Harm Model Error Detection Abilities
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If you delete all errors, the model may lose the ability to detect and correct errors
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Claude Code becomes an IDE-native teammate
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This is Claude Code turning into an IDE native teammate.
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Machine Learning Refined: Foundations, Algorithms, and Python Applications
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#MachineLearning Refined — Foundations, #Algorithms, and Applications (with 100 in-depth coding exercises in #Python): http://
amzn.to/3EblXVx —————
#Coding #DataScience #ML #AI #DeepLearning #NeuralNetworks #Mathematics #DataScientist -
Stanford’s Free Machine Learning Courses Available Online
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From @swapnakpanda Stanford’s FREE Machine Learning Courses: CS221 – Artificial Intelligence
CS229 – Machine Learning
CS230 – Deep Learning
CS234 – Reinforcement Learning
CS224N – NLP with Deep Learning Links below… -
Comprehensive Python Machine Learning Book Third Edition 772 Pages
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Learn Python for #MachineLearning comprehensively in this massive 772-page book:
=> #Python Machine Learning (3rd Ed.)
=> http://
amzn.to/42eUuhB by @rasbt ————
#DataScience #ML #AI #NeuralNetworks #DeepLearning #DataScientist #ReinforcementLearning -
Building Neo4j-Powered Applications with LLMs and Haystack
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New from @PacktDataML >> "Building Neo4j-Powered Applications with LLMs: Create LLM-driven search and recommendations applications with Haystack, LangChain4j, and Spring AI" Available at https://
amzn.to/4l9lLKO