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A Guide to Evaluating MCP-powered LLM Apps
...explained with step-by-step code.
17 hrs ago
•
Avi Chawla
3
How Dropout Actually Works
A lesser-known detail of Dropout.
Sep 10
•
Avi Chawla
5
Building An Enterprise-grade Document Parser
100% local, beats GPT-4o.
Sep 9
•
Avi Chawla
6
Train Neural Nets 4-6x Faster!
Explained with code and visuals.
Sep 8
•
Avi Chawla
2
1
Data and Pipeline Engineering (With Implementation)
The full MLOps/LLMOps blueprint.
Sep 6
•
Avi Chawla
7
[Hands-on] MCP-powered Agentic RAG
...explained step-by-step with code.
Sep 5
•
Avi Chawla
0:28
Build a Reasoning LLM using GRPO
...explained step-by-step with code.
Sep 4
•
Avi Chawla
4
0:10
7 LLM Generation Parameters
...explained visually
Sep 3
•
Avi Chawla
3
3
8 Key LLM Development Skills for AI Engineers
...covered with resources and explained visually.
Sep 2
•
Avi Chawla
11
[Hands-on] Audio RAG with 200x Cheaper Vector DB Costs
...while also outperforming OpenAI and Cohere.
Sep 1
•
Avi Chawla
2
0:28
August 2025
Data and Pipeline Engineering for ML Systems (With Implementation)
The full MLOps/LLMOps blueprint.
Aug 30
•
Avi Chawla
7
Build Production-grade MCP Servers
...in less than a minute and no-code.
Aug 29
•
Avi Chawla
7
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