DeepLearning.ai Releases a Free Course on Building Applications with Vector Databases

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New Course Alert: Vector Databases

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1. Semantic Search App

[{"selector":"#anim-f3d3e93b-973c-48e3-aacb-79973e6b48a8","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-3e11fbcb-0c20-4ef0-8717-113101032d16","keyframes":{"transform":["translate3d(0px, 208.11490%, 0)","translate3d(0px, 0px, 0)"]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-3d59d278-2103-411f-bd71-eb4512b88d88","keyframes":{"opacity":[0,1]},"delay":120,"duration":1300,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] [{"selector":"#anim-84f79d2f-8f3f-41a3-9d8c-312b6d61b8af","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] Learn to build a Semantic Search tool, focusing on content's meaning over keywords, using a user Q/A dataset. Image source: Canva

2. RAG for LLM

[{"selector":"#anim-4eac9818-fdb4-4a18-975f-a954817060b4","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-ec5bcd7d-f773-43fd-b9b2-68db0e1da1a6","keyframes":{"transform":["translate3d(0px, 201.35795%, 0)","translate3d(0px, 0px, 0)"]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-a43c7d64-c41b-4f36-9038-0df504d76ce3","keyframes":{"opacity":[0,1]},"delay":120,"duration":1300,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] [{"selector":"#anim-92b5a46e-449e-447b-9d3b-5984a743e3b9","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] Enhance LLMs with RAG, answering queries with untrained data like Wikipedia, for accurate, detailed responses. Image source: Canva

3. Recommender System

[{"selector":"#anim-94754081-d278-497c-bee6-08a42d40ae38","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-d3c72d58-370a-4690-9aec-09218b8a415b","keyframes":{"transform":["translate3d(0px, 201.37335%, 0)","translate3d(0px, 0px, 0)"]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-1cec4334-18d1-4737-8c0a-417ce40b7fef","keyframes":{"opacity":[0,1]},"delay":120,"duration":1300,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] [{"selector":"#anim-34644d5f-8076-4524-9191-7fadd9c29588","keyframes":{"opacity":[0,1]},"delay":120,"duration":1200,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] Create a Recommender System that leverages semantic search and RAG for topic suggestions, using news articles. Image source: Canva

4. Hybrid Search

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5. Facial Similarity

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6. Anomaly Detection

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Beyond RAG: The Power of Vector Databases

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Who Should Enroll?

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Join the Future of Application Development

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