Advanced Retrieval Augmented Generation

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[ FreeCourseWeb.com ] Advanced Retrieval Augmented Generation
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction & Setup
    • 1 - 000_INTRO_post_processed.mp4.mp4 (120.7 MB)
    • 2 - 00_SETUP_01_OPENAI_API_KEY.mp4.mp4 (34.8 MB)
    • 3 - 00_SETUP_02_INSTALL_VIRTUAL_ENV_JUPYTER.mp4.mp4 (16.5 MB)
    • 4 - 00_SETUP_03_DOCKER_LANGFUSE.mp4.mp4 (52.3 MB)
    • 5 - 00_SETUP_04_CREATE_REPO_FOR_OUR_CODE.mp4.mp4 (27.9 MB)
    2 - Section 1 - Making our LLM powered systems more Robust
    • 1 - 01_ROBUSTNESS_01_PROTECT_API_KEY_WITH_DOTENV.mp4.mp4 (61.5 MB)
    • 10 - fname 01_ROBUSTNESS_10_Update_Wrappertscproj.mp4.mp4 (43.9 MB)
    • 11 - 01_ROBUSTNESS_11_TRACING_LANGFUSE.mp4.mp4 (217.3 MB)
    • 12 - 01_ROBUSTNESS_12_Tracing+Caching.mp4.mp4 (51.0 MB)
    • 13 - 01_ROBUSTNESS_13_Retrying_Decorator.mp4.mp4 (129.7 MB)
    • 14 - 01_ROBUSTNESS_14_Demo_Retry_and_putting_it_all_together.mp4.mp4 (120.0 MB)
    • 15 - 01_ROBUSTNESS_15_theory_structured_outputs_agentic_patterns_post_processed.mp4.mp4 (56.2 MB)
    • 16 - 01_ROBUSTNESS_16_STRUCTURED_OUTPUTS_DEMO_post_processed.mp4.mp4 (135.7 MB)
    • 17 - 01_ROBUSTNESS_17_Robust_Structured_Outputs_post_processed.mp4.mp4 (219.8 MB)
    • 18 - 01_ROBUSTNESS_18_Section_Conclusion_post_processed.mp4.mp4 (20.2 MB)
    • 2 - 01_ROBUSTNESS_02_CALLING_AN_OPENAI_LLM.mp4.mp4 (128.5 MB)
    • 3 - 01_ROBUSTNESS_03_THEORY_TOKENS.mp4.mp4 (27.9 MB)
    • 4 - 01_ROBUSTNESS_04_THEORY_LLM.mp4.mp4 (23.5 MB)
    • 5 - 01_ROBUSTNESS_04_ASYNCHRONOUS_CODE.mp4.mp4 (144.9 MB)
    • 6 - 01_ROBUSTNESS_06_THE_FIVE_PROBLEMS_WE_NEED_TO_SOLVE (1).mp4.mp4 (80.7 MB)
    • 7 - 01_ROBUSTNESS_07_Caching_DISKCACHE.mp4.mp4 (94.1 MB)
    • 8 - 01_ROBUSTNESS_08_Caching_LLM_Calls_Cached.mp4.mp4 (228.8 MB)
    • 9 - 01_ROBUSTNESS_09_ignore_cache_dir.mp4.mp4 (12.7 MB)
    3 - Section 2 - Measure and Improve Performance of the Retrieval System
    • 1 - 02_RETRIEVAL_01_SECTION_INTRODUCTION_post_processed.mp4.mp4 (75.8 MB)
    4 - Section 2 - Part 1 - Generating a Synthetic Evaluation Dataset
    • 1 - 02_RETRIEVAL_02_DATASET_INTRODUCTION_post_processed.mp4.mp4 (56.6 MB)
    • 2 - 02_RETRIEVAL_03_LOAD_DATASET_post_processed.mp4.mp4 (37.1 MB)
    • 3 - 02_RETRIEVAL_04_HOW_TO_GENERATE_post_processed.mp4.mp4 (45.5 MB)
    • SECTION_02_01_EVALUATION_DATA_GENERATION_.ipynb.ipynb (7.5 KB)
    • paul_allen_sent_emails.csv.csv (164.2 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Advanced Retrieval Augmented Generation

https://FreeCourseWeb.com

Published 8/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 27m | Size: 2.2 GB

How to make Advanced RAG work in practice with Evaluations, Agentic Patterns and Generative AI with LLM

What you'll learn
You will learn how to increase the robustness of you LLM calls by implementing structured outputs, acing, caching and retries
How to generate synthetic data to establish a baseline for your RAG system, even if your RAG system don't have users yet
How to filter out redundant generated data
How to make all your LLM calls faster AND cheaper using asynchronous Python and caching
How to not be held back by OpenAI rate limits

Requirements
Have Docker installed on your machine
Access to a modern powerful laptop with python installed or a Google Drive account
Working experience as a Software Engineer, preferrably more than two years
At least intermediate Python Programming or the ability to learn it fast (eg: Seniority in another Programming Language)
Willing to spend about ten dollars for running the LLM calls (either locally or through OpenAI)
Access to pro version of ChatGPT (or equivalent)
Basic of data science (precision, recall, pandas)
Ability to debug by yourself, especially typos (we will use async code, you must be comfortable reading tracebacks)
You know what RAG means and have already implemented Basic or Naive RAG in a tutorial, at least



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Advanced Retrieval Augmented Generation

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2.2 GB
seeders:5
leechers:14
Advanced Retrieval Augmented Generation

Torrent hash: F911F072B3DF12FC9393B6344F868D02E20316AF