Navigating via Retrieval Evaluation to Demystify LLM Wonderland
Explore retrieval evaluation's crucial role in LLM applications, focusing on its impact on response quality. Delve into the link between retrieval accuracy and answer quality, emphasizing thorough evaluation methods.
RAG and RecSys - Parallels in Retrieval Quality Improvement
Explore parallels between RAG and recommender systems, focusing on improving retrieval quality through hybrid reranking techniques using LanceDB in this concise AI production talk.
The Role of ML Engineers in the Era of GPT-4 and BARD
Explore the evolving role of ML engineers amid the rise of large language models. Learn to evaluate API suitability, address privacy concerns, and adapt skills for future projects.
Solving LLM Data Problems with Vector Databases - Part 2
Explore vector databases' role in LLM apps, focusing on solving data issues and democratizing access to this technology for efficient billion-scale vector search.
Taming AI Product Development Through Test-driven Prompt Engineering
Explore test-driven development's crucial role in prompt engineering for AI systems. Learn to create reliable, predictable AI products through effective TDD practices.
Building a Python-Centric Feature Platform to Power Production AI Applications
Explore Tecton's journey in developing a Python-based platform for powering large-scale real-time AI applications. Learn about reliable solutions for productionizing AI using only Python skills.
Productionizing Health Insurance Appeal Generation - AI in Production
Explore fine-tuning models for health insurance appeals, cloud resource utilization, and on-premises Kubernetes deployment. Learn about unexpected challenges in server setup and graphics card installation.
Fine-Tune T5 for Document Classification - Part 1: Creating Dataset with Web Scraping
Personalize Flan-T5 for document classification by creating a custom dataset using web scraping techniques with DuckDuckGo.
Serving Flask and FastAPI Applications in Google Colab
Aprenda a servir aplicações Flask ou FastAPI no Google Colab ou na nuvem, utilizando técnicas de ciência de dados e aprendizado de máquina.
Neo4J Graph Data Science: Load Data Using GDS
Upload data to Neo4J using Graph Data Science Library. Learn efficient techniques for data integration in graph databases for machine learning and data science applications.
Vertex AI: Gemini Pro Multimodal Chatbot - Creating Conversational AI with Python SDK
Create a conversational multimodal chatbot using Vertex AI, Gemini Pro 1.5, and Python SDK. Learn to implement advanced AI capabilities for interactive and visual-based conversations.
Installing WSL with CUDA Support and PyTorch for Data Science and Machine Learning
Aprenda a instalar WSL con soporte CUDA y PyTorch para potenciar sus proyectos de aprendizaje automático y ciencia de datos en Windows.
Creating a QA Tool Using Langchain, OpenAI, and Neo4J
Develop a QA tool using Langchain, Neo4J, and OpenAI models for advanced data science and machine learning applications.
Counting Tokens with OpenAI's Tiktoken Library for API Usage
Learn to count tokens consumed by OpenAI's API using the Tiktoken library, optimizing your usage and costs.
MLOps with MLflow - Creating Execution Pipelines Using Projects and Databricks
Explore MLflow Projects to create execution pipelines locally and leverage Databricks for tracking and artifact storage in machine learning workflows.
Document Similarity: Langchain, Ollama Mistral 7B, and Chroma for Machine Learning and Data Science
Explore document similarity using Langchain, Ollama with Mistral 7B or LLama 2, and Chromadb as VectorStore for machine learning and data science applications.
Whisper OpenAI Speech-to-Text and Translation Model
Aprende a utilizar Whisper, el modelo de reconocimiento de voz de OpenAI, para transcribir y traducir audio con precisión.
Computer Vision: OCR Tesseract for Different Formats and File Types
Extract text from various image and document formats using OCR Tesseract. Learn practical techniques for optical character recognition in data science and machine learning applications.
Introduction to Amazon Bedrock - AWS Machine Learning and Data Science
Explore Amazon Bedrock, AWS's managed serverless service for Generative AI and LLMs. Learn key features and applications in machine learning and data science.
How to Install Conda for Data Science and Machine Learning
Aprenda a instalar Anaconda y dominar los entornos conda para ciencia de datos y aprendizaje automático.
Neo4J GDS: Node Embeddings Algorithms for Data Science and Machine Learning
Explore node embedding algorithms in Neo4J GDS for data science and machine learning, creating powerful graph-based representations.