Transformer Architecture Explained: Attention, Training, and GPU Setup
Content1 Key Points2 Prerequisites3 What Are Transformers?4 Transformer Architecture: Detailed, Step-by-Step5 Attention: The Core Math (Concise)6 Scaled Dot-Product Attention7 Multi-Head Attention (MHA)8 Masked Attention9 Residuals, LayerNorm, and Stability10 Output Projection…
Data Augmentation in Machine Learning: Image, Text & Audio Techniques
Content1 Key Takeaways2 Why Use Data Augmentation?3 Image Augmentation Techniques4 Setting Up an Augmentation Pipeline5 Adding Gaussian Noise to Images6 Load and Prepare the Data7 Apply Gaussian Noise Augmentation8 Display…
OpenAI gpt-oss Explained: Architecture, MXFP4 Quantization & 120B/20B Models
Content1 Model Variants and Hardware Requirements2 Key Takeaways3 Model Architecture4 Quantization5 Tokenizer6 Post-training Focus7 OpenAI Harmony Chat Format8 Additional Resources9 Final Thoughts Vijona4 Feb at 10:15 OpenAI gpt-oss: Architecture, Quantization,…
Embedding-Free RAG: Alternatives to Vector Databases for Retrieval-Augmented Generation
Content1 Key Takeaways2 Traditional RAG and Vector Databases3 Limitations of Embeddings & Vector Search4 What Is RAG Without Embeddings?5 Lexical or Keyword-Based Retrieval6 LLM-based Iterative Search (Reasoning as Retrieval)7 Structured…
RAG vs MCP: When to Use Retrieval or Tool-Based Actions with LLMs
Content1 Key Takeaways2 Prerequisites3 Understanding RAG and MCP4 When RAG Is the Best Fit5 When MCP Is the Best Fit6 Potential Failure Modes to Watch For7 Choosing Between RAG and…
Offline Vibe Coding with Local LLMs: Tools, Models, and Workflows
Content1 Key Takeaways2 The Best Local Agentic LLMs in May, 20263 Hosting the Models Locally4 Coding with Local Large Language Models5 Conclusion Vijona19 May at 9:30 Vibe Coding and the…
Advanced Bash Scripting Guide: Automation, Optimization & Linux System Mastery
Content1 Going Beyond Basic Shell Scripts in Linux2 Key Takeaways for Advanced Shell Scripting3 Readability and Maintainability4 Error Handling5 Debugging Techniques6 Leveraging Advanced Shell Features7 Regular Expressions and Pattern Matching8…
PyTorch vs TensorFlow vs ONNX: ML Deployment Guide
Content1 Key Takeaways for ML Tools and Deployment Workflows2 PyTorch: Flexible Training and Research-Oriented Design3 TensorFlow: Production-Ready Framework and Comprehensive Ecosystem4 TensorFlow End-to-End: From Model Development to Deployment5 LiteRT: Lightweight…
Cloud Snapshot Misuse: Costs, Copy-on-Write, and Prevention
Content1 Key Takeaways2 How Copy-on-Write Snapshots Work3 How Snapshot Misuse Happens4 Why Limiting Snapshots and Resizing Matters5 Toward a Fairer Model: Smarter Snapshot Management6 A Note on Drawbacks7 FAQs8 Conclusion…