| 1 -14. Introduction to the architecture used in LLM.mp4 | 36.9 MB | ||
| 1 -19. Introduction to Transformers - Tokenization.mp4 | 39.1 MB | ||
| 1 -25. Lab 1 - Building a chabot using Huggingface.mp4 | 92.2 MB | ||
| 1 -3. What is Generative AI.mp4 | 23.7 MB | ||
| 1 -30. Evaluation Metrics - The BLEU Score.mp4 | 75.8 MB | ||
| 1 -9. Introduction to LLMs.mp4 | 12.6 MB | ||
| 1 -Introduction.mp4 | 59.1 MB | ||
| 2 -10. Understanding language is not easy.mp4 | 13.2 MB | ||
| 2 -15. Fully Connected Networks.mp4 | 133 MB | ||
| 2 -2. Course Content.mp4 | 23 MB | ||
| 2 -20. Python demo on Tokenization.mp4 | 36.4 MB | ||
| 2 -26. Inferencing Parameters - top p, top k, temperature.mp4 | 57.6 MB | ||
| 2 -31. Evaluation Metrics - The ROUGE score.mp4 | 35.4 MB | ||
| 2 -4. Example - Difference between GenAI and Discriminative AI.mp4 | 25.3 MB | ||
| 3 -11. LLM Demo.mp4 | 17.3 MB | ||
| 3 -16. Neural Networks are Function Approximators.mp4 | 62.7 MB | ||
| 3 -21. Embedding - Words in the vector space.mp4 | 97.4 MB | ||
| 3 -27. Demo on Inferencing Parameters.mp4 | 33.2 MB | ||
| 3 -32. In Context Learning - Zero shot, few shot, One shot Inferences.mp4 | 68.7 MB | ||
| 3 -5. A review on Probability Terms, Bayes theorem.mp4 | 94.7 MB | ||
| 4 -12. What does an LLM do.mp4 | 18.7 MB | ||
| 4 -17. Introduction to RNN.mp4 | 55.1 MB | ||
| 4 -22. Overview on the working of the Encoder-Decoder.mp4 | 83.4 MB | ||
| 4 -28. Lab 2 - Sentiment Analysis.mp4 | 66.1 MB | ||
| 4 -6. Case Study Introduction - Digit Recognition.mp4 | 15.4 MB | ||
| 5 -13. Applications of an LLM.mp4 | 4.4 MB | ||
| 5 -18. RNN - A deep dive.mp4 | 70.4 MB | ||
| 5 -23. Self Attention - Full Explanation on the QKV Matrix.mp4 | 118.6 MB | ||
| 5 -29. Lab 3 - Building a simple translator.mp4 | 45.1 MB | ||
| 5 -7. Case Study Introduction - Digit Recognition (Contd.).mp4 | 40.7 MB | ||
| 6 -18.1 - Pretraining vs Finetuning.mp4 | 55.7 MB | ||
| 6 -24. Embedding - Demo.mp4 | 50.7 MB | ||
| 6 -8. Summary on GenAI.mp4 | 39.4 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 35 total files | |||
Generative AI and Large Language Models
https://WebToolTip.com
Published 6/2025
Created by Sujithkumar MA
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 33 Lectures ( 4h 34m ) | Size: 1.67 GB
A beginner-friendly guide to Generative AI and LLMs covering transformer basics, and hands-on python labs
What you'll learn
Understand the Fundamentals of Machine Learning and Generative AI
Gain Practical Knowledge of Large Language Models (LLMs)
Perform Hands-on Tasks Using Python and Hugging Face
Evaluate and Tune LLM Outputs Effectively
Requirements
No programming experience needed
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 2.6 GB | freecoursewb | 4 days | 0 | 0 | |
| 779 MB | freecoursewb | 1 week | 1 | 25 | |
| 1.3 GB | freecoursewb | 1 week | 1 | 5 | |
|
Udemy - Designing with Generative AI - Figma, Midjourney and ChatGPT Posted by
freecoursewb in Other
|
1.2 GB | freecoursewb | 1 week | 0 | 0 |
| 484.5 MB | freecoursewb | 1 week | 1 | 6 |
All Comments