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Plan Szkolenia
Introduction to Vector Databases
- Understanding vector databases
- Key features and benefits of Milvus
- Comparison with traditional databases
Setting Up Milvus
- Installation and configuration
- Understanding Milvus components and architecture
- Creating collections and partitions
Data Indexing and Management
- Indexing strategies in Milvus
- Managing and optimizing vector data
- Best practices for data ingestion
Similarity Search and Retrieval
- Fundamentals of similarity search
- Implementing search operations in Milvus
- Use cases: image and video retrieval, NLP
Milvus in Machine Learning (ML)
- Integrating Milvus with ML models
- Building recommendation systems
- Case studies: anomaly detection, chatbots
Scalability and Performance
- Scaling Milvus for large datasets
- Performance tuning and optimization
- Monitoring and maintenance
Implementing Milvus in AI
- Developing a vector database solution
- Review and feedback
Summary and Next Steps
Wymagania
- Basic understanding of databases
- Introductory knowledge of AI and machine learning concepts
- Familiarity with programming concepts, preferably in Python
Audience
- Data scientists
- Software developers
- Machine learning enthusiasts
21 godzin
