Udemy LLM Concepts Deep Dive Conceptual Mastery for Developer
Seeders : 23 Leechers : 12
| Torrent Hash : | 464EFD664C59DF26987C248B6A050C7425876A12 |
| Torrent Added : | at May 8, 2025, 3:11 p.m. in Other |
| Torrent Size : | 3.6 GB |
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Udemy LLM Concepts Deep Dive Conceptual Mastery for Developer
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Please Update (Trackers Info) Before Start " Udemy LLM Concepts Deep Dive Conceptual Mastery for Developer" Torrent Downloading to See Updated Seeders And Leechers for Batter Torrent Download Speed.Torrent File Content (3 files)
Udemy LLM Concepts Deep Dive Conceptual Mastery for Developer
Get Bonus Downloads Here.url -
1 -Understanding the Concept of Model.mp4 -
2 -Language Model Tasks and Auto Encoding.mp4 -
3 -Auto Regression and Text Prediction.mp4 -
4 -Text completion.mp4 -
5 -Audience Questions.mp4 -
1 -Pre-training.mp4 -
2 -Instruct tuning.mp4 -
3 -Fine Tuning.mp4 -
4 -Audience Questions.mp4 -
5 -Introduction to Fine-Tuning AI Models.mp4 -
1 -Introduction to Tokens and Embeddings.mp4 -
10 -Audience Questions.mp4 -
2 -Tokenization Explained.mp4 -
3 -Visualizing Tokenization.mp4 -
4 -How token boundaries are formed.mp4 -
5 -How word frequencies are identified.mp4 -
6 -Embeddings and Their Importance.mp4 -
7 -Exploring Embeddings and the N-dimensional space.mp4 -
8 -Embedding Math. Mind-Blowing Examples.mp4 -
9 -Tokenization and Embeddings.mp4 -
1 -Quiz Time Test Your Knowledge.mp4 -
2 -The Concept of Text Similarity.mp4 -
3 -Audience Questions.mp4 -
1 -From Tokens To Text.mp4 -
2 -Introduction to Transformer Architecture.mp4 -
3 -Understanding Attention in LLMs.mp4 -
4 -Addressing Questions on Transformer Architecture.mp4 -
1 -Introduction to Context Length in LLMs.mp4 -
2 -Challenges with Context Limit and Statelessness.mp4 -
1 -Introducing Retrieval Augmented Generation (RAG).mp4 -
2 -Some important terminologies.mp4 -
3 -Vector Databases and Their Role in RAG.mp4 -
4 -How Vector Databases Work.mp4 -
5 -Vector Database Interaction Pseudocode.mp4 -
6 -The RAG Pipeline.mp4 -
7 -Q&A and Final Thoughts.mp4 -
Bonus Resources.txt -
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Get Bonus Downloads Here.url -
180 bytes
1 -Understanding the Concept of Model.mp4 -
114.2 MB
2 -Language Model Tasks and Auto Encoding.mp4 -
79.0 MB
3 -Auto Regression and Text Prediction.mp4 -
121.6 MB
4 -Text completion.mp4 -
78.4 MB
5 -Audience Questions.mp4 -
127.1 MB
1 -Pre-training.mp4 -
144.6 MB
2 -Instruct tuning.mp4 -
156.8 MB
3 -Fine Tuning.mp4 -
88.1 MB
4 -Audience Questions.mp4 -
72.3 MB
5 -Introduction to Fine-Tuning AI Models.mp4 -
38.9 MB
1 -Introduction to Tokens and Embeddings.mp4 -
71.5 MB
10 -Audience Questions.mp4 -
29.3 MB
2 -Tokenization Explained.mp4 -
133.5 MB
3 -Visualizing Tokenization.mp4 -
26.6 MB
4 -How token boundaries are formed.mp4 -
220.3 MB
5 -How word frequencies are identified.mp4 -
112.9 MB
6 -Embeddings and Their Importance.mp4 -
314.9 MB
7 -Exploring Embeddings and the N-dimensional space.mp4 -
116.6 MB
8 -Embedding Math. Mind-Blowing Examples.mp4 -
58.0 MB
9 -Tokenization and Embeddings.mp4 -
76.5 MB
1 -Quiz Time Test Your Knowledge.mp4 -
124.6 MB
2 -The Concept of Text Similarity.mp4 -
106.2 MB
3 -Audience Questions.mp4 -
71.1 MB
1 -From Tokens To Text.mp4 -
151.1 MB
2 -Introduction to Transformer Architecture.mp4 -
109.7 MB
3 -Understanding Attention in LLMs.mp4 -
137.8 MB
4 -Addressing Questions on Transformer Architecture.mp4 -
101.2 MB
1 -Introduction to Context Length in LLMs.mp4 -
70.9 MB
2 -Challenges with Context Limit and Statelessness.mp4 -
132.9 MB
1 -Introducing Retrieval Augmented Generation (RAG).mp4 -
124.0 MB
2 -Some important terminologies.mp4 -
68.1 MB
3 -Vector Databases and Their Role in RAG.mp4 -
88.6 MB
4 -How Vector Databases Work.mp4 -
71.7 MB
5 -Vector Database Interaction Pseudocode.mp4 -
32.6 MB
6 -The RAG Pipeline.mp4 -
41.1 MB
7 -Q&A and Final Thoughts.mp4 -
62.6 MB
Bonus Resources.txt -
70 bytes
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