Langchain: Conversational QA Tool with Gemini, Langchain, and Faiss
Crea un chatbot de preguntas y respuestas conversacional utilizando Langchain, Gemini Pro 1.5, Faiss y Vertex AI para consultar una base de conocimientos personalizada.
Llama 2, Ollama and Pinecone - Vector Database Search for Machine Learning and Data Science
Explore embedding and searching text using Llama 2, Ollama, and Pinecone Vector Database for efficient information retrieval in machine learning projects.
Building a RAG Application with GitHub Models and Postgres from Scratch
Learn to build a Retrieval Augmented Generation (RAG) application from scratch using GitHub Models and PostgreSQL, enhancing AI model capabilities for smarter applications.
A Deterministic Algorithm for Balanced Cut with Applications to Dynamic Connectivity, Flows, and Beyond
Explore deterministic algorithms for balanced cut, with applications in dynamic connectivity and network flows. Learn about two-way reduction, competition games, and embedding techniques.
Natural Language Processing with Deep Learning and TensorFlow
Explore deep learning for NLP using TensorFlow. Learn to create embeddings, build neural networks, and apply them to classification tasks with hands-on labs and interactive learning.
NLP for Security Log Analysis - Learning to Crawl Before You Run
Explore the application of NLP in security analysis, focusing on embeddings for insider threat detection and the impact of large language models on the field.
How We Built a Job Recommender SaaS with Deep Learning to Disrupt the Job Market
Discover how deep learning and modern ML tools were used to create a multilingual job recommender system, revolutionizing job matching for a public employment service.
Mining Software Development History - Approaches and Challenges
Explore software development history analysis, including embeddings, time warping, and clustering techniques. Learn to extract insights from version control logs and predict future trends.
NoSQL Data Modeling for Front-end Developers
Learn NoSQL data modeling techniques for front-end developers to improve API design, application flow, and performance while avoiding common pitfalls in flexible schema databases.
Machine Learning on Go Code
Explore machine learning applications for Go code, including embeddings, code completion, and bug prediction. Discover how ML can enhance developer productivity and code quality.
Vector Databases and Large Language Models for Context Retrieval - LLMs in Production
Explore vector databases and LLMs for real-time context retrieval in AI applications. Learn to enhance generative models with up-to-date external knowledge, preventing hallucinations and improving accuracy.
Monitoring Unstructured Data - Lightning Session
Explore ML observability for unstructured data with Arize. Learn about embeddings, monitoring challenges, and solutions through expert insights and a product demo.
The Capabilities of Semantic Search
Explore semantic search capabilities with the Jina framework, covering symbolic vs. semantic approaches and practical applications for various data types.
Understanding Task Vectors in Vision-Language Models - Cross-Modal Representations
Explore how Vision-Language Models create task vectors - internal representations enabling cross-modal performance through text and images, revolutionizing AI's ability to understand and execute diverse tasks.
Building a Chatbot Web Interface Using Large Language Models and RAG
Dive into building chatbots with OpenAI models, exploring retrieval augmented generation (RAG), and learn practical implementation strategies for creating an effective knowledge base interface.
Beyond AI Vector Database - Neural Search Implementation with GPT-4 and ChatGPT
Discover how to build a cost-effective neural search system using tokenizers, embedders, and similarity calculations as an alternative to Azure Cognitive Search for domain-specific AI applications.
Embedding by Unembedding - Extending HOAS for Complex Semantic Domains
Explore a novel language development technique that extends HOAS, addressing limitations in semantic domains for open expressions, with applications in incremental computation and bidirectional languages.
Tutorial de Bases de Datos Vectoriales, LangChain y ChatGPT
Aprende a integrar bases de datos vectoriales, LangChain y ChatGPT para crear aplicaciones de IA avanzadas y eficientes.
Vertex AI Embeddings API and Matching Engine - Grounding LLMs for Enterprise Use
Explore grounding LLMs using Vertex AI Embeddings API and Matching Engine. Learn key concepts for building reliable generative AI services in enterprise environments.
BigQuery Vector Search and Embedding Generation for Semantic Analysis
Unlock semantic search with BigQuery: transform unstructured data into embeddings, enabling powerful analysis and connections beyond traditional keyword searches.
Understanding Generative AI: RAG, Semantic Search, Embeddings, and Vectors
Explore key Generative AI concepts like RAG, semantic search, embeddings, and vectors. Understand their importance in leveraging AI with your data for improved information retrieval and processing.