Building Apps with Fine-tuned LLMs Using Google Vertex AI and Generative AI Studio
Discover how to build AI-powered apps using Vertex AI's Generative Studio - fine-tune LLMs on enterprise data, deploy models, and create applications without coding while exploring new career opportunities.
Schema Generation for Querying a Data Lakehouse
Explore schema generation techniques using LLMs for data lakehouse querying, focusing on GraphQL implementation, knowledge infusion, and reasoning capabilities for effective data retrieval.
Cilium Overview - Introduction to Cloud-Native Networking with eBPF
Discover how Cilium leverages eBPF technology for cloud-native networking and security, exploring key features and implementation strategies for modern infrastructure.
SaFeR: A Safety Framework for e-Scooter Riders
Explore a comprehensive safety framework for e-scooter riders, featuring real-time monitoring systems, deep learning algorithms, and adaptive safety metrics for enhanced urban micromobility.
Getting the Best of Both Worlds - IoT and Edge Using Hierarchical Inference
Explore hierarchical inference strategies for optimizing IoT and edge computing, focusing on machine fault detection and image classification while balancing accuracy with resource constraints.
Trends and Challenges in Multi-cloud Networking and Observability
Explore challenges and solutions in multi-cloud networking, focusing on application-aware connectivity, AI-based analytics, and intelligent automation across distributed cloud environments.
Machine Learning Debug Tutorial - Fall 2023
Master essential debugging techniques for machine learning algorithms, focusing on practical troubleshooting methods and common error resolution in ML development.
Teaching Vector Databases at Scale
Discover how vector databases are being integrated into university curricula and online learning platforms, with insights on implementing RAG patterns and scaling database education.
Building the Ultimate Hybrid Search with Qdrant - A Hands-on Tutorial
Master advanced semantic search techniques by transforming dense embedding pipelines into hybrid systems with Qdrant's latest features, including ColBERT models and universal search endpoints.
How Vector Search with Qdrant Improves Workplace Efficiency
Discover how vector search technology and Qdrant power modern work environments, exploring implementation, scaling challenges, and practical applications in AI-driven business solutions.
Indexify Unveiled: A Scalable Content Extraction Engine for Multimodal Data
Discover how Indexify enables scalable content extraction and real-time knowledge base creation for AI workflows, focusing on unstructured data processing and hybrid search capabilities.
Superpower Your Semantic Search Using Vector Database - From Model Architecture to Deployment
Discover how to enhance matching systems using vector databases, focusing on implementation, deployment, and optimization for improved search performance and scalability in production environments.
High-Performance Entity Matching Solution Using Vector Embeddings and AWS
Discover how to build a high-performance hotel matching system using vector embeddings, AWS infrastructure, and Qdrant for efficient data processing and improved accuracy in the travel industry.
Binary Quantization Methods for Vector Database Optimization
Dive into vector database optimization through binary quantization, exploring compression techniques, search speed improvements, and practical implementation strategies for efficient vector similarity search.
Building a Semantic Search App for Music Using Qdrant Cloud
Learn to develop a semantic search application using Qdrant Cloud's Python SDK to efficiently search through thousands of songs across different music genres.
Music Recommendation System with Qdrant Vector Search and Audio Embeddings
Learn to build a music recommendation engine using Qdrant's vector search capabilities, audio embeddings, and metadata to create personalized song suggestions.
Image Classification with Qdrant Vector Semantic Search for Medical Diagnosis
Learn to build an image-based semantic search engine for skin condition diagnosis using Qdrant, covering embedding generation and vector database implementation.
Natural Language Processing with Qdrant for Vector Similarity Search
Master vector similarity search using Qdrant to create embeddings from text data, perform contextual searches, and build recommendation systems for enhanced natural language processing applications.
Getting Started with Qdrant - Introduction to Vector Database and Similarity Search
Master vector similarity search using Qdrant to build semantic search and recommendation systems through hands-on practice with sample datasets and practical implementations.
Qdrant Vector Database and Search Engine Implementation in Rust
Dive into vector database technology with Qdrant, exploring its architecture, implementation in Rust, and applications in similarity search, matching, and recommendations systems.
Embeddings and Similarity Search with Qdrant Vector Database
Explore vector embeddings and similarity search concepts through hands-on demonstrations using Qdrant database, with practical examples for implementing efficient search solutions.