pca

Author: alelapi

docs/gcp/cheatsheets/ai-ml.md

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+# AI/ML Essentials
+
+## 🎯 Heavy Hitters (High Frequency)
+
+### 1. **Vertex AI Agent Builder**
+
+- **What**: Low-code platform to build GenAI chatbots/conversational AI
+- **When**: Customer support bots, RAG applications, enterprise chatbots
+- **Key Feature**: Connects to data sources (websites, docs) automatically
+- **Exam Clue**: "Build a chatbot quickly without coding" → Agent Builder
+
+### 2. **Vector Search**
+
+- **What**: Find semantically similar content (not just keyword matching)
+- **Use Cases**: 
+  - Semantic search ("find similar products")
+  - Image similarity ("find visually similar images")
+  - Recommendation engines
+- **Two Options**:
+  - **Vertex AI Vector Search**: Standalone, managed service
+  - **AlloyDB + pgvector**: If data already in AlloyDB/PostgreSQL
+- **Exam Clue**: "semantic", "similar", "embeddings" → Vector Search
+
+### 3. **Securing AI**
+
+- **Model Armor**: Filters toxic/harmful AI outputs before reaching users
+- **VPC Service Controls**: Creates security perimeter around Vertex AI to prevent data exfiltration
+- **Exam Clue**: "Prevent training data leakage" → VPC-SC
+
+---
+
+## 🧠 Core Vertex AI Concepts
+
+### **Model Garden**
+
+- **What**: Marketplace/"App Store" for AI models
+- **Options**: Google's Gemini, OSS (Llama, Claude), third-party models
+- **When**: Client needs to compare/choose between different model providers
+- **Exam Clue**: "Evaluate multiple models" → Model Garden
+
+### **Gemini Cloud Assist**
+
+- **What**: AI-powered operations assistant
+- **Use Cases**:
+  - GKE cost optimization recommendations
+  - Network troubleshooting
+  - Quick infrastructure insights
+- **Exam Clue**: "Quickly optimize/troubleshoot infrastructure" → Cloud Assist
+
+---
+
+## 📊 Data-to-AI Workflow
+
+### **BigQuery ML**
+
+- **When**: Data already in BigQuery + simple ML (regression/classification)
+- **Benefit**: No data movement, SQL-based ML
+- **Exam Clue**: "Data in BQ, simple prediction" → BQML
+- **Not For**: Complex deep learning, image/video models
+
+### **Vertex AI Pipelines**
+
+- **What**: MLOps orchestration (automated training/retraining workflows)
+- **When**: Need repeatable, production ML pipelines with CI/CD
+- **Components**: Kubeflow Pipelines or TFX
+- **Exam Clue**: "Automate model retraining", "MLOps" → Pipelines
+
+---
+
+## 🔒 AI Security (Critical for PCA)
+
+### **VPC Service Controls (AI Context)**
+
+- **What**: Security perimeter preventing data from leaving your environment
+- **Use With**: Vertex AI, BigQuery, Cloud Storage
+- **Exam Clue**: "Prevent data exfiltration during training" → VPC-SC
+- **Setup**: Create perimeter → Add projects → Restrict egress
+
+### **Sensitive Data Protection (DLP)**
+
+- **What**: Identify and redact PII/sensitive data
+- **Use Cases**:
+  - Redact names/SSNs before model training
+  - De-identify healthcare data (HIPAA)
+  - Scan datasets for PII
+- **Methods**: Masking, tokenization, redaction
+- **Exam Clue**: "Remove PII before training" → DLP API
+
+---
+
+## 🎓 Exam Decision Tree
+
+```
+Question mentions "chatbot" → Agent Builder
+Question mentions "semantic/similar" → Vector Search
+Question mentions "data leakage prevention" → VPC Service Controls
+Question mentions "PII removal" → DLP
+Data in BigQuery + simple ML → BigQuery ML
+Need automated retraining → Vertex AI Pipelines
+Compare multiple models → Model Garden
+Quick infra optimization → Gemini Cloud Assist
+```
+
+---
+
+## ⚡ Quick Reminders
+
+- **Vertex AI** = Unified ML platform (training, deployment, monitoring)
+- **Embeddings** = Vector representations → Use Vector Search
+- **RAG** = Retrieval Augmented Generation → Agent Builder + Vector Search
+- **MLOps** = Pipelines + Monitoring + Continuous training
+- **Security Layers**: VPC-SC (network) + DLP (data) + Model Armor (output)