freeCodeCamp via YouTube Free video
Learn how to benchmark embedding models on your own data in this course for beginners.
In this course, you will learn:
- The limitations of extracting text from PDF files with Python libraries and to solve that with the help of VLMs (Vision Language Models).
- How to divide the extracted text into chunks that preserve context.
- Generation questions for each chunk using LLMs (Large Language Models).
- Use embedding models to create vector representations of the chunks and questions.
- Use both open source and proprietary embedding models.
- Use llama.cpp to run models in the GGUF format locally on your machine.
- Perform the benchmarking of different embedding models using various metrics and statistical tests with the help of ranx.
- Plot the vector representations to visualize if clusters are being formed.
- Understand how to interpret the p-value that a statistical test provides.
- And much more!
You can find the slides, notebook, and scripts in this GitHub repository:
https://github.com/ImadSaddik/Benchmark_Embedding_Models
The dataset is available here:
https://huggingface.co/datasets/ImadSaddik/BenchmarkEmbeddingModelsCourse
To connect with Imad Saddik, check out his social accounts:
LinkedIn: https://www.linkedin.com/in/imadsaddik/
YouTube: https://www.youtube.com/@3CodeCampers
Website: https://imadsaddik.com/
⭐️ Course Contents ⭐️
(0:00:00) About the course
(0:06:05) Introduction
(0:17:58) Extracting text from PDF documents
(1:01:08) Divide text into coherent chunks
(1:23:10) Generate question-answer pairs from text chunks
(1:38:48) Embed text chunks and questions
(2:17:06) Statistical tests and metrics
(3:12:01) Expanding the dataset and adding more languages
(3:45:24) Conclusion
Some points apply to every course of this kind; see how we rank.
freeCodeCamp is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (78/100). Free full courses and certifications; practical, but not university-level depth.
Instructor: Prof. Gary Gensler View the complete course: https://ocw.mit.edu/15-S12F18 This course is for students wishing to explore blockchain technology’s potential use - by entrepreneurs & incumbents - to change the world of money and finance. License: Creative Commons BY-NC-SA More information…
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performa…
This is CS50P, CS50's Introduction to Programming with Python. Register for free at https://cs50.edx.org/python. Slides and source code at https://cs50.harvard.edu/python. Playlist at https://www.youtube.com/playlist?list=PLhQjrBD2T3817j24-GogXmWqO5Q5vYy0V. An introduction to programming using a la…
This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches…
Instructor: Ana Bell View the complete course: https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/ *Note: Lectures 6, 10 have been updated! This subject is aimed at students with little to no programming experience. It aims to provide students with an under…
Get more information about the courses and programs we offer. In this playlist you can learn more about course content, pricing, credentials and more!
