Data Science & ML

Recent Data Science & ML articles

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8 articles

Discover our latest articles and guides on Data Science & ML

MLOps interview questions illustrated with an MLflow model registry, deployment pipeline, and drift monitoring dashboard on a dark background
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MLOps in 2026: MLflow, Model Registry and Technical Interview Questions

MLOps interview questions covering the ML lifecycle, MLflow experiment tracking, model registry promotion, deployment patterns, drift monitoring, and system design for 2026, with Python code and answers.

RAG retrieval-augmented generation pipeline architecture with vector database and LLM
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RAG and LLMs in 2026: Retrieval-Augmented Generation for Data Science Interviews

Retrieval-Augmented Generation (RAG) explained for data science interviews in 2026. Covers vector databases, chunking strategies, embedding models, agentic RAG, Graph RAG, and production-ready pipeline architecture.

Hugging Face Transformers NLP fine-tuning tutorial 2026
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Hugging Face Transformers in 2026: NLP, Fine-Tuning and Interview Questions

Hugging Face Transformers tutorial covering the v5 API, fine-tuning with LoRA, NLP pipelines, and the most common interview questions asked in data science roles in 2026.

Feature engineering for machine learning: data transformation pipeline visualization
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Feature Engineering for Machine Learning: Techniques and Interview Questions 2026

Master feature engineering for machine learning with practical Python examples. Covers encoding, scaling, feature selection, scikit-learn pipelines, and common data science interview questions.

PyTorch vs TensorFlow deep learning framework comparison 2026
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PyTorch vs TensorFlow in 2026: Which Deep Learning Framework Should You Choose?

PyTorch vs TensorFlow comparison for 2026 covering performance benchmarks, deployment options, ecosystem maturity, and real-world use cases to help pick the right deep learning framework.

Python data science tutorial with NumPy Pandas and Scikit-Learn code and dashboards illustration
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Python for Data Science: NumPy, Pandas and Scikit-Learn in 2026

A hands-on tutorial covering NumPy array operations, Pandas data manipulation, and Scikit-Learn model training. Build a complete data pipeline from raw CSV to trained model with production-ready Python code.