Professional
AutoML: Evaluation & Debugging
Your AutoML model is trained. Is it good? interpreting Confusion Matrices, Precision/Recall curves, and Feature Importance to fix underperforming models.
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Engineering Articles
59 posts
Engineering
AI in the SDLC: What Actually Works vs Slideware
Move beyond the hype and discover the real value of AI in the Software Development Life Cycle. This guide walks through an ideal AI-augmented dev loop, from drafting specs to incident review.
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Professional
Google Cloud ML APIs: AI Without Training
When to skip training altogether. A guide to the Vision, Natural Language, Translation, and Speech APIs. Learn the 'Pre-trained' strategic advantage.
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Engineering
The Microservices Moment for AI: Designing Multi-Agent Systems That Don’t Melt Down
Treating AI agents like microservices is the key to building stable, scalable multi-agent systems. Learn about routing, retries, and monitoring in the age of agentic AI.
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Engineering
RAG Is Not a Database: Common Retrieval-Augmented Gen Mistakes (and How to Fix Them)
Building a RAG system that works in production is harder than it looks. Avoid common mistakes like bad chunking and missing metadata by understanding that RAG is a dynamic system, not just a static database.
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Professional
BigQuery ML: Machine Learning with SQL
Why move data when you can bring the model to the data? Learn to build Classification, Regression, and Time-Series models directly within BigQuery using standard SQL.
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Professional
BigQuery ML: Feature Engineering
How to preprocess data using SQL. Learn to use the TRANSFORM clause, ML.Bucketing, ML.Scaling, and One-Hot Encoding directly in BigQuery.
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Professional
BigQuery ML: Predictions & Deployment
How to get answers. Using ML.PREDICT, ML.EXPLAIN_PREDICT, and exporting BQML models to Vertex AI for online serving.
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Professional
The Professional ML Engineer: What to Expect
Your roadmap to passing the Google Cloud Professional ML Engineer certification. We break down the exam structure, the case study format, and the mindset shift from 'Data Scientist' to 'ML Engineer'.
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