Simplifying Data Ingestion for LLMs with Unstructured and Databricks
Learn to build a scalable solution for unstructured data ingestion in LLM applications using Unstructured and Databricks, addressing challenges and exploring efficient methods.
The AI of Where - Unleashing the Power of GenAI on Geospatial Data
Explore cutting-edge GenAI applications in location intelligence, enhancing spatial data analysis. Learn innovative uses of Large Language Models and Segment Anything Model for geospatial datasets, with real-world examples and case studies.
Moving from SAP Business Warehouse to Databricks - Insurance Company Case Study
Explore an insurance company's migration from SAP BW to Databricks, highlighting improved performance, automated ETL, enhanced self-service, and cost reduction. Learn insights and future possibilities.
AI Business Ideas Funded by Y Combinator - Analysis and Insights
Explore YCombinator-funded AI business ideas, analyzing industry trends, B2B vs B2C, infrastructure vs applications, and untapped opportunities for AI disruption and innovation.
GumGum Media's Data Science Journey on Databricks
Explore GumGum Media's data science evolution with Databricks, featuring insights from Sr. Engineering Manager Brendan Frick on leveraging advanced analytics for media innovation.
Creating a Data and GenAI Ecosystem - Migrating to Databricks
Gerdau's journey to create a flexible, simplified Data and GenAI ecosystem using Databricks, resulting in cost reduction, tool consolidation, and improved governance for the steel industry.
Data Engineering on the Data Intelligence Platform - A Comprehensive Guide
Explore data engineering on Databricks' platform: ingest, transform, and orchestrate data at scale. Learn about streaming pipelines, data quality, and AI-powered tools for real-time insights.
AI for Sustainable Logistics and Supply Chain Management
Explore AI's role in sustainable logistics and supply chain management, covering CO2 reduction, efficiency, optimization, resilience, and security from academic and industry perspectives.
Cross-Validation Revisited: Evaluating Machine Learning Models with Non-IID Data
Explore challenges and techniques for evaluating machine learning models with non-IID data, focusing on spatial autocorrelation, concept drift, and phylogenetic non-independence.
Coresets for Robust Submodular Maximization with Deletions
Explore submodular maximization against deletions, learning about coresets and algorithms for robust optimization in data science problems. Gain insights from Nikolaj Tatti's research on streaming and offline approaches.
Quantifying Determinants of Microbial Growth
Explore computational approaches for quantifying microbial growth determinants, focusing on genotype-environment interactions and their implications for pathogen control and biotechnology.
Challenges of Future Supply Chain Management - Possibilities of AI
Explore AI's role in addressing future supply chain challenges, focusing on sustainability, efficiency, and resilience in logistics management.
A Guided Tour of Interactive Jupyter Notebooks Powered by nanoHUB
Explore interactive Jupyter Notebooks on nanoHUB. Learn fundamentals, develop code, analyze data, create visualizations, and build GUIs using Jupyter widgets and nanohub-uidl library.
Document Similarity Using Langchain, OpenAI Embeddings, and Neo4J
Explore document similarity using Langchain, Neo4j, and OpenAI embeddings. Learn practical techniques for machine learning and data science applications.
LLMOps: LLMs Memory and Compute Optimizations
Explore FlashAttention, GQA, FSDP, and DDP techniques to enhance LLM efficiency, training, and fine-tuning in self-attention layers.
Prompt Engineering Techniques with Mistral 7B Instruct for Data Science and Machine Learning
Explore prompt engineering techniques using Mistral 7B Instruct, including zero-shot, few-shot, CoT, and RAG. Learn to craft effective prompts for enhanced machine learning outcomes.
MLOps: Using Python Libraries in DotNet - Spacy, Numpy, Pandas
Integrate Python libraries like Spacy, NumPy, and Pandas into .NET applications using Pythonnet for enhanced machine learning and data science capabilities.
Microsoft AI: Semantic Kernel and RAG Dynamic Prompts with C# - Data Science and Machine Learning
Explore RAG component creation using Dynamic Prompts with Microsoft Semantic Kernel, utilizing Ollama Framework and Phi3 Mini model in C#.
Creating Synthetic Data with Langchain, OpenAI, and Faker
Generate synthetic data using Langchain, OpenAI, and Faker for data science and machine learning applications. Learn powerful techniques to create realistic datasets.
LLMOps: Quantization Models and Inference with ONNX Generative Runtime
Explore ONNX runtime GPU support for inference with generative models, including Phi3-mini quantization and conversion techniques.
Neo4J Knowledge Graph Builder App with Langchain, OpenAI, and Gemini
Build knowledge graphs from unstructured data using Neo4J's Knowledge Graph Builder App with AI integration for efficient data extraction and visualization.