:Search:

Udemy Master AI Agent Development LangChain OpenAI Ollama

Torrent:
Info Hash: 0EAAD3C2182098AE40DB32714AF587D276B50431
Similar Posts:
Uploader: freecoursewb
Source: 1 Logo 1337x
Type: Tutorials
Language: English
Category: Other
Size: 3.8 GB
Added: Oct. 23, 2025, 10:07 p.m.
Peers: Seeders: 5, Leechers: 19 (Last updated: 5 months, 3 weeks ago)
Tracker Data:
Tracker Seeders Leechers Completed
udp://open.stealth.si:80/announce 0 0 0
udp://exodus.desync.com:6969/announce 0 6 0
udp://tracker.cyberia.is:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.opentrackr.org:1337/announce 2 6 0
udp://tracker.torrent.eu.org:451/announce 0 0 0
udp://explodie.org:6969/announce 2 7 0
udp://tracker.birkenwald.de:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.moeking.me:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://ipv4.tracker.harry.lu:80/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.therarbg.to:6969/announce 1 0 0
Files:
  1. Get Bonus Downloads Here.url 180 bytes
  2. 1 - What is MCP - MCP.pptx 954.0 KB
  3. 1 - What is MCP.mp4 168.4 MB
  4. 2 - Understanding FASTMCP A Python Framework for Building and Developing MCP.mp4 100.5 MB
  5. 3 - Building a FastMCP setup integrated with a local database and an Ollama Agent - server.py 2.4 KB
  6. 3 - Building a FastMCP setup integrated with a local database and an Ollama Agent.mp4 343.1 MB
  7. 1 - Understanding Embeddings in the world of NLP - embeddings.pptx 1.2 MB
  8. 1 - Understanding Embeddings in the world of NLP.mp4 159.1 MB
  9. 2 - Running Our First Local LLM using Qwen Model - app.py 469 bytes
  10. 2 - Running Our First Local LLM using Qwen Model - requirements.txt 13 bytes
  11. 2 - Running Our First Local LLM using Qwen Model.mp4 89.7 MB
  12. 3 - Building a RAG-powered Assistant with LLaMA 3.1 using Pinecone - llama-rag.ipynb 6.9 KB
  13. 3 - Building a RAG-powered Assistant with LLaMA 3.1 using Pinecone.mp4 312.2 MB
  14. 4 - Deepseek Coder Assistant - app.py 6.0 KB
  15. 4 - Deepseek Coder Assistant - requirements.txt 32 bytes
  16. 4 - Deepseek Coder Assistant.mp4 124.4 MB
  17. 1 - LangChain Agents - Guide.docx 15.2 KB
  18. 1 - LangChain Agents - Recording 2025-09-17 080254.mp4 48.4 MB
  19. 1 - LangChain Agents - agent.ipynb 74.3 KB
  20. 1 - LangChain Agents - requirements.txt 169 bytes
  21. 1 - LangChain Agents.mp4 70.8 MB
  22. 2 - AI Voice Agent Emotion Analysis & Wellness Companion - app.py 5.0 KB
  23. 2 - AI Voice Agent Emotion Analysis & Wellness Companion - requirements.txt 165 bytes
  24. 2 - AI Voice Agent Emotion Analysis & Wellness Companion.mp4 162.4 MB
  25. 3 - Virtual AI Based Talking Agents.mp4 80.4 MB
  26. 4 - AI Copilot Agent - agent.ipynb 3.7 KB
  27. 4 - AI Copilot Agent - app.py 667 bytes
  28. 4 - AI Copilot Agent.mp4 133.3 MB
  29. 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - app.py 1.9 KB
  30. 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - main.py 1.2 KB
  31. 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS - whisper.py 1.6 KB
  32. 5 - Building a Voice-to-GPT Agent with Streamlit, FastAPI, Whisper & TTS.mp4 134.2 MB
  33. 6 - AI Fitness & Diet Planner Agent - app.py 2.1 KB
  34. 6 - AI Fitness & Diet Planner Agent.mp4 106.9 MB
  35. 1 - Hugging Face Tutorial.mp4 138.8 MB
  36. 2 - Exploring the GPT-2 Model and Understanding Custom Datasets with Hugging Face.mp4 146.6 MB
  37. 3 - Deep Understanding of Language Models - Language Models.pptx 1.8 MB
  38. 3 - Deep Understanding of Language Models.mp4 105.2 MB
  39. 4 - Inside Transformer Architecture How It Works - Transformer Model.pptx 3.0 MB
  40. 4 - Inside Transformer Architecture How It Works.mp4 229.4 MB
  41. 1 - PyTorch Core Principles and Foundations - Introduction_to_PyTorch.pdf 789.2 KB
  42. 1 - PyTorch Core Principles and Foundations.mp4 200.1 MB
  43. 1 - What is LlamaIndex & its Use-Cases.mp4 125.2 MB
  44. 1 - Mastering Fine-Tuning Exploring Types & Techniques in the LLM Era - fine-tuning.pptx 817.5 KB
  45. 1 - Mastering Fine-Tuning Exploring Types & Techniques in the LLM Era.mp4 133.4 MB
  46. 2 - Fine-Tuning VS RAG - fine-tuning-vs-RAG.pptx 1.0 MB
  47. 2 - Fine-Tuning VS RAG.mp4 83.8 MB
  48. 3 - Hands-On Fine-Tuning From Theory to Practice - fine-tuning.ipynb 48.1 KB
  49. 3 - Hands-On Fine-Tuning From Theory to Practice.mp4 448.0 MB
  50. 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud - app2.py 1.2 KB
  51. 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud - ollama_with_ngrok.ipynb 102.1 KB
  52. 1 - Deploy the Gemma model on Google Colab & expose it to the web using Ngrok cloud.mp4 207.3 MB
  53. Bonus Resources.txt 70 bytes

Discussion