atulkrs/mlops-devops-sentiment

MLOps & DevOps Sentiment Dataset

Dataset description

A domain-specific sentiment dataset containing real-world MLOps and DevOps scenarios labeled as POSITIVE or NEGATIVE. Built to fine-tune sentiment classifiers for technical operations contexts where general-purpose models (trained on movie reviews) underperform.

Why this dataset exists

General sentiment models misclassify technical sentences. For example:

• —"The pipeline failed silently" → general models often miss the negativity
• —"Terraform rollback was effortless" → domain context needed for high confidence

Dataset structure

Fields

• —text — sentence describing an MLOps/DevOps scenario
• —label — 0 (NEGATIVE) or 1 (POSITIVE)
• —domain — mlops or devops
• —text_length — word count (added during preprocessing)

Source

Manually curated by @atulkrs based on real-world MLOps and DevOps engineering experience.

Usage

\\\python from datasets import load_dataset ds = load_dataset("atulkrs/mlops-devops-sentiment") print(ds["train"][0]) \\\

Intended use

• —Fine-tuning sentiment classifiers for MLOps/DevOps tooling feedback
• —Benchmarking domain adaptation of general NLP models
• —Curriculum data for MLOps-aware LLM fine-tuning