1 Introduction - Course prerequisites and structure.mp4 (63.96 MB)
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1 Pinecone - Deep Dive.mp4 (38.75 MB)
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10 Section Summary.mp4 (23.38 MB)
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2 Create Pinecone Account & Dashboard Overview.mp4 (25.02 MB)
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3 Creating our Pinecone Index in Code.mp4 (31.51 MB)
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4 Upserting and Querying our Pinecone Index.mp4 (47.69 MB)
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5 Querying Pinecone Manually in the Dashboard.mp4 (25.85 MB)
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6 Using LangChain Pinecone Wrapper - Create Index and Upsert & Similarity Search.mp4 (97.6 MB)
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7 Creating a Retriever and Chain Objects & a LLM to get a Response.mp4 (72.68 MB)
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8 Clean up - Delete Pinecone Index.mp4 (15.46 MB)
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9 Challenge - Explore other Vector Database.mp4 (21.19 MB)
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1 Choosing the Right Vector Database - Comparison Tables.mp4 (71.27 MB)
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2 Which Database Should I Choose.mp4 (45.74 MB)
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3 Choosing the Right Database - Criterias.mp4 (83.28 MB)
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1 Congratulations and Next Steps.mp4 (71.01 MB)
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1 Introduction to Vector Databases - Full Overview.mp4 (85.44 MB)
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2 Why Vector Databases.mp4 (204.51 MB)
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3 Vector Databases - Benefits and Advantages.mp4 (57.46 MB)
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1 Traditional vs Vector Databases - Limitations and Challenges.mp4 (110.43 MB)
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2 Embeddings vs Vectors - Differences.mp4 (57.13 MB)
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3 Vector Databases - How They Work and Advantages.mp4 (61.38 MB)
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4 Vector Databases Use Cases.mp4 (100.77 MB)
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5 Vector and Traditional Databases - Summary.mp4 (9.86 MB)
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1 The Top 5 Vector Databases - Overview.mp4 (142.64 MB)
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2 Understanding LLM (Large Language Models).mp4 (29.21 MB)
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1 Development Environment Setup.mp4 (18.3 MB)
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10 Vector Databases Metrics and Data Structures.mp4 (73.11 MB)
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11 Section Summary.mp4 (13.87 MB)
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2 Setup VS-Code, Python and OpenAI API Key.mp4 (45.87 MB)
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3 Chroma Database workflow.mp4 (126.61 MB)
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4 Creating a Chroma Vector Database & Adding Documents & Querying them.mp4 (70.37 MB)
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5 Looping Through the Results & Showing Similarity Search Results.mp4 (54.75 MB)
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6 Chroma Default Embedding Function.mp4 (55.93 MB)
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7 Chroma Vector Database - Persisting Data and Saving.mp4 (86.07 MB)
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8 Creating an OpenAI Embeddings - Raw without Chroma.mp4 (74.29 MB)
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9 Using OpenAIs Embedding API to Create Embedding in Chroma.mp4 (97.27 MB)
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1 Vector Similarity Deep Dive - Cosine Similarity.mp4 (29.38 MB)
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2 Euclidean Distance - L2 Norm.mp4 (25.21 MB)
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3 Dot Product.mp4 (35.72 MB)
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4 Section Summary.mp4 (19.83 MB)
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1 Vector Databases and LLM - Deep Dive.mp4 (67.45 MB)
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2 Loading all Documents.mp4 (76.7 MB)
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3 Generating Embeddings from Documents & Insert then into Chroma Database.mp4 (91.62 MB)
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4 Getting the Relevant Chunks when Given a Query.mp4 (67.68 MB)
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5 Using OpenAI LLM to Generate Response - Full Flow.mp4 (74.7 MB)
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6 Section Summary.mp4 (26.23 MB)
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1 The LangChain Framework - Quick Overview.mp4 (42.04 MB)
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2 Getting started with LangChain and the OpenAIChat Wrapper.mp4 (51.82 MB)
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3 Loading Documents with LangChain Document Loader.mp4 (73.75 MB)
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4 Splitting the Documents with LangChain.mp4 (14.52 MB)
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5 Creating a Chroma Vector Database with LangChain.mp4 (48.46 MB)
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6 Getting the Response from the Model - the Complete WorkFlow.mp4 (94.42 MB)
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