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The Training LanceDB - Optimize 3D Vector Searches training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
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The assessment of skills acquired during the Training LanceDB - Optimize 3D Vector Searches training is carried out through:
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Discover quick installation of LanceDB via Docker and pip, configure collections for embeddings from Blender 3D models, perform first vector inserts on exported meshes, test native Python connections, practice exercises on real 3D datasets to validate setup, generate initial performance reports, integrate sharding concepts for enterprise scalability.
Dive into vector indexing with IVF-PQ and HNSW on 3D embeddings from Maya/3ds Max, optimize parameters for high recall precision, generate indexes on millions of 3D vectors, compare QPS/latency metrics via practical benchmarks, integrate 3D metadata for hybrid filters, develop automated batch indexing scripts, analyze real business cases for production workflows.
Master advanced kNN queries on embedded Cinema 4D datasets, implement hybrid reranking for relevant results, fuse vector scores/3D metadata, test real-time queries on remote clusters, optimize for low-latency via caching, develop RESTful API for Blender integration, evaluate precision via NDCG metrics on real business cases, generate 3D visualizations of results.
Deploy LanceDB in Kubernetes cluster mode for massive 3D production, integrate Prometheus/Grafana monitoring for performance alerts, secure access via JWT auth, migrate Blender/Maya datasets to production, test high-availability failover, develop CI/CD pipelines with GitHub Actions, finalize capstone project on certified 3D vector search, receive personalized feedback for business skills.
Target audience
3D graphic designers, data engineers, Blender/Maya developers, ML engineers in companies seeking to upskill on vector databases
Prerequisites
Proficiency in Python, knowledge of vector embeddings, basics in 3D modeling with Blender or Maya, experience with NoSQL databases
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