RAG (Retrieval)

4h 33m 19s
English
Paid

Course description

Study the key principles of developing Retrieval-Augmented Generation (RAG) systems and the application of advanced search techniques to improve the performance of artificial intelligence. As part of the course, you will master the integration of RAG into AI applications, optimization of information retrieval and answer generation processes, and learn to apply advanced machine learning technologies to enhance the accuracy and efficiency of intelligent systems.

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#1: 1.1 Intro

All Course Lessons (22)

#Lesson TitleDurationAccess
1
1.1 Intro Demo
09:32
2
1.2 RAG Overview
12:58
3
1.3 Code Setup
08:39
4
1.4 Embeddings
12:08
5
1.5 Vector Databases
20:42
6
1.6 Similarity Search
08:12
7
2.1 Intro
08:38
8
2.2 Vector DB Setup
19:07
9
2.3 Generating Embeddings
12:35
10
2.4 Uploading Data
08:05
11
2.5 Basic Retrieval
11:57
12
2.6 Query Optimization
09:41
13
2.7 Document Reranking
10:59
14
2.8 Metadata Filtering
11:03
15
2.9 Text Splitting
08:36
16
2.10 All Together
09:27
17
2.11 RAG Prompting
12:44
18
3.1 Project Intro
09:19
19
3.2 Initialize Code
06:50
20
3.3 Setup Vector DB
12:03
21
3.4 Build RAG Pipeline
27:48
22
3.5 Connect Frontend
22:16

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