Mlops

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Ryan Giggs

Jan 15

OCI Generative AI: Dedicated Cluster Sizing, Pricing, and Fine-Tuning Deep Dive

#ocigenai #finetuning #mlops #clustersizing

9 min read

Aun Raza

Jan 10

What an AI Engineering Lead Actually Does in 2026 (Beyond Models and Prompts)

#ai #mlops #engineering #production

6 min read

Jayanth Dasari

Dec 19 '25

Day-10

#bash #devops #cloud #mlops

1 min read

Hossein Mortazavi

Dec 3 '25

Running Microsoft's Phi-3 on CPU with Rust & Candle

#rust #mlops #ai #python

5 min read

ASHISH GHADIGAONKAR

Dec 3 '25

Why Accuracy Lies — The Metrics That Actually Matter (Part 4)

#machinelearning #mlops #modelevaluation #ai

2 min read

ASHISH GHADIGAONKAR

Dec 3 '25

Bias–Variance Tradeoff — Visually and Practically Explained (Part 6)

#machinelearning #mlops #modelevaluation #ai

3 min read

ASHISH GHADIGAONKAR

Dec 3 '25

How to Architect a Real-World ML System — End-to-End Blueprint (Part 8)

#machinelearning #mlops #modelevaluation #ai

3 min read

ASHISH GHADIGAONKAR

Dec 3 '25

ML Observability & Monitoring — The Missing Layer in ML Systems (Part 7)

#machinelearning #mlops #modelevaluation #ai

3 min read

ASHISH GHADIGAONKAR

Dec 3 '25

Overfitting & Underfitting — Beyond Textbook Definitions (Part 5)

#machinelearning #mlops #modelevaluation #ai

2 min read

Dechun Wang

Dec 31 '25

Stop Parsing Nightmares: Prompting LLMs to Return Clean, Parseable JSON

#llm #ai #promptengineering #mlops

9 min read

ASHISH GHADIGAONKAR

Dec 1 '25

The Hidden Failure Point of ML Models — Part 1

#machinelearning #mlops #datascience #ai

3 min read

Imran Siddique

Dec 29 '25

Beyond Fine-Tuning: Architecting the Self-Evolving Agent

#aiautonomousagents #aiarchitecture #mlops #graphrag

4 min read

NACAMURA Mitsuhiro

Nov 24 '25

"As Cloud-like as Possible" Data Science: Local MLOps with Docker Compose

#datascience #docker #mlops #mlflow

3 min read

AppRecode

Dec 24 '25

MLOps Best Practices (10 Practical Practices Teams Actually Use)

#mlops #mlopsservices #mlopspractices

13 min read

ASHISH GHADIGAONKAR

Dec 2 '25

Data Leakage — The Silent Accuracy Killer (Part 2)

#machinelearning #mlops #datascience #ai

3 min read

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DEV Community

# mlops

OCI Generative AI: Dedicated Cluster Sizing, Pricing, and Fine-Tuning Deep Dive

What an AI Engineering Lead Actually Does in 2026 (Beyond Models and Prompts)

Day-10

Running Microsoft's Phi-3 on CPU with Rust & Candle

Why Accuracy Lies — The Metrics That Actually Matter (Part 4)

Bias–Variance Tradeoff — Visually and Practically Explained (Part 6)

How to Architect a Real-World ML System — End-to-End Blueprint (Part 8)

ML Observability & Monitoring — The Missing Layer in ML Systems (Part 7)

Overfitting & Underfitting — Beyond Textbook Definitions (Part 5)

Stop Parsing Nightmares: Prompting LLMs to Return Clean, Parseable JSON

The Hidden Failure Point of ML Models — Part 1

Beyond Fine-Tuning: Architecting the Self-Evolving Agent

"As Cloud-like as Possible" Data Science: Local MLOps with Docker Compose

MLOps Best Practices (10 Practical Practices Teams Actually Use)

Data Leakage — The Silent Accuracy Killer (Part 2)