Practical GraphRAG - Making LLMs Smarter with Knowledge Graphs
Explore GraphRAG: enhancing LLMs with knowledge graphs for improved context and accuracy in generative tasks. Learn to extract, correlate, and navigate data using Neo4j and LangChain.
Supercharge Your Java Applications with Python
Enhance Java apps with Python using GraalPy. Embed Python code, install packages, and explore use cases like AI integration, data visualization, and multilingual scripting in Java projects.
Spring AI: Seamlessly Integrating AI into Enterprise Java Applications
Integrate AI into Java enterprise apps using Spring AI. Learn key concepts, develop AI applications rapidly, and explore practical use cases like semantic search and RAG patterns.
Exploring the Power of ChatGPT: Revolutionizing AI Applications
Unlock ChatGPT's potential in AI applications, from creative tasks to secure software development. Explore its capabilities, security implications, and transformative impact across various industries.
Data Versioning in Generative AI: A Pathway to Cost-Effective ML
Explore data versioning strategies for Generative AI, focusing on managing large-scale unstructured data and optimizing resource usage in model scoring and API interactions.
Introduction to LangChain and Retrieval Augmented Generation (RAG)
Explore LangChain's core concepts and build LLM-based applications using Retrieval Augmented Generation for document-based question answering.
How Many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks?
Explore the effectiveness of in-context learning vs. labelled data for predictive tasks, comparing BERT-sized models to GPT-4 in text categorization and entity recognition.
Supercharging Search with Language Models (LLMs)
Explore how Instacart revolutionized search using Language Models, enhancing user experience with personalized recommendations and improved results.
Building Your LLM Factory
Discover strategies for integrating LLMs into enterprise infrastructure, overcoming challenges, and leveraging cloud computing for AI applications.
Your AI Applications Need Guardrails: How to Build Them
Learn to build robust guardrails for AI applications, ensuring consistent and accurate outputs from Large Language Models in production environments.
Getting Higher ROI on MLOps Initiatives
Discover five key lessons for building cohesive MLOps platforms, enhancing self-service capabilities, and maximizing return on investment in machine learning operations.
Fine-Tune LLMs or Integrate 3rd Party APIs? A Financial Case Study
Explore LLM integration strategies for MLOps, comparing fine-tuning and API use. Learn key considerations, challenges, and risk mitigation techniques for implementing advanced language models.
Retrieval Augmented Generation with LangChain: ChatGPT for Your Data - Part 2
Explore Retrieval Augmented Generation using LangChain. Learn to build and optimize question-answering systems with vector stores, embedding models, and LLMs for private data applications.
Engineering an LLM Application: Chat with MLOps World
Develop a chatbot using MLOps World content, exploring techniques to transform it from concept to production-ready application.
Retrieval Augmented Generation with LangChain: ChatGPT for Your Data - Part 1
Explore Retrieval Augmented Generation using LangChain to build a question-answering system with private data, leveraging vector stores, embedding models, and LLMs.
Supercharge Your Java Applications with Python
Enhance Java apps with Python using GraalPy. Explore embedding Python in Java, integrating AI libraries, and leveraging multi-language capabilities for data science and machine learning.
Making ChatGPT Funny with Prompt Optimization - MLOps World
Discover techniques to enhance ChatGPT's humor through prompt engineering, overcoming AI limitations and unlocking its comedic potential.
Synthetic Data: Generative AI for Enhanced Data Quality in the Era of Foundational Models
Explore synthetic data's transformative potential in AI, focusing on data quality, augmentation, bias, and privacy for foundational language models.
Customizable RAG Workflows with Your Own Data
Build customizable RAG workflows using OSS tools and your own data to optimize GenAI applications for corporate environments. Learn best practices and advanced techniques.
Introducing Arize-Phoenix and OpenInference for AI Evaluation and Observability
Explore AI observability and evaluation with OpenInference and Arize-Phoenix. Learn practical techniques for incorporating LLMs to guard against hallucinations and poor retrieval.
Evaluation Engineering: Iterative Strategies to Testing Prompts
Explore iterative strategies for testing prompts, including backtesting and regression testing, to enhance evaluation engineering in prompt development.