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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
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mcp guide.pdf.pdf
16.7 MB
A comprehensive PDF has been compiled that includes all MCP-related posts shared over the past six months.

(75 pages, 10+ projects & visual explainers)

Over the last half year, content has been published about the Modular Computation Protocol (MCP), which has gained significant interest and engagement from the AI community. In response to this enthusiasm, all tutorials have been gathered in one place, featuring:

* The fundamentals of MCP
* Explanations with visuals and code
* 11 hands-on projects for AI engineers

Projects included:

1. Build a 100% local MCP Client
2. MCP-powered Agentic RAG
3. MCP-powered Financial Analyst
4. MCP-powered Voice Agent
5. A Unified MCP Server
6. MCP-powered Shared Memory for Claude Desktop and Cursor
7. MCP-powered RAG over Complex Docs
8. MCP-powered Synthetic Data Generator
9. MCP-powered Deep Researcher
10. MCP-powered RAG over Videos
11. MCP-powered Audio Analysis Toolkit

#MCP #ModularComputationProtocol #AIProjects #DeepLearning #ArtificialIntelligence #RAG #VoiceAI #SyntheticData #AIAgents #AIResearch #TechWriting #OpenSourceAI #AI #python

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๐Ÿ“Œ Evaluating Synthetic Data โ€” The Million Dollar Question

๐Ÿ—‚ Category: DATA SCIENCE

๐Ÿ•’ Date: 2025-11-07 | โฑ๏ธ Read time: 13 min read

How can you trust your synthetic data? Answering this "million dollar question" is crucial for any AI/ML project. This article details a straightforward method for evaluating synthetic data quality: the Maximum Similarity Test. Learn how this simple test can help you measure how well your generated data mirrors real-world information, building confidence in your models and ensuring the reliability of your results.

#SyntheticData #DataScience #MachineLearning #DataQuality