InData Science + AI at MicrosoftbyJames Nguyen·Mar 5Effective long-term memory for AI agents: Lessons from human cognitionAI agents are transforming how businesses interact with customers — from financial advisors that remember your investment goals to…A response icon1A response icon1
InData Science + AI at MicrosoftbyJames Nguyen·Apr 16, 2024Toward learning-capable LLM agentsPresenting the concept and design principles behind developing LLM agents that possess the capability to learnA response icon1A response icon1
InData Science + AI at MicrosoftbyJames Nguyen·Nov 18, 2023Forget RAG: Embrace agent design for a more intelligent grounded ChatGPT!The Retrieval Augmented Generation (RAG) design pattern has been commonly used to develop a grounded ChatGPT in a specific data domain…A response icon21A response icon21
InData Science + AI at MicrosoftbyJames Nguyen·Jul 4, 2023Automating data analytics with ChatGPTAs an AI language model, ChatGPT is becoming well known for its ability to generate text-based responses to given prompts and contextual…A response icon7A response icon7
InAnalytics VidhyabyJames Nguyen·Mar 29, 2022Teaching Machine Learning System Efficiently with Active LearningA response icon1A response icon1
James Nguyen·Jun 23, 2021Implementing Many Models at Scale with Spark 3.x (Databricks/Synapse) and Azure MLThere are many scenarios where we need to build and run a large number of machine learning models. For examples: in Retail where a separate…A response icon1A response icon1
James Nguyen·Feb 19, 2021Best practices in Enterprise Data Science governance in AzureNow that your enterprise data science is on Azure, you can take advantage of cloud agility and a set of great tools to improve development…
James Nguyen·Oct 4, 2020Directly Reading Delta Lake Data from Azure SynapseAzure Databricks and Azure Synapse Analytics are two flagship big data solutions in Azure. Many customers use both solutions. Databricks…A response icon3A response icon3
InAnalytics VidhyabyJames Nguyen·Sep 16, 2019Leveraging Spark for Large Scale Deep Learning Data Preparation and InferencingWhile it has been been know training a Deep Learning model requires lots of data to produce good result, rapidly growing business data…A response icon2A response icon2
