Articles / Topic guide
Topic guide
Data flows, streaming, anomaly detection, ETL, and operational foundations for AI and ML systems.
For organizations where the AI problem starts with scattered, slow, or hard-to-govern data.
Related articles
Jun 2026 · LLMs & Agents
Use Python, Pydantic, and the Instructor library to extract structured data from unstructured text. Parse invoices and job postings into typed, validated Python objects reliably and at scale.
Read
Jun 2026 · LLMs & Agents
Build an autonomous data analysis agent using LangGraph. Learn how agents differ from RAG, and implement the ReAct loop with tools for querying and summarizing data.
Read
Jun 2026 · MLOps
Go from fragile training scripts to robust, observable ML workflows using Prefect. Schedule retraining, handle failures gracefully, and monitor every run.
Read
Jun 2026 · MLOps
Learn how to detect data drift and model degradation in production using Evidently AI. Build automated reports and alerts before your model silently fails.
Read
May 2026 · Machine Learning
A step-by-step guide to building your first ML model: data exploration, preprocessing, cross-validation, hyperparameter tuning, and evaluation: all with scikit-learn.
ReadMay 2026 · Operations Research
Use pyworkforce to assign work shifts and minimize the gap between required and scheduled resources, with built-in support for preferences, banned shifts, and rest rules.
ReadApr 2026 · Machine Learning
Explore how to use ExponentialAdapter and InverseAdapter in sklearn-genetic-opt to dynamically adjust mutation and crossover probabilities.
ReadApr 2026 · Machine Learning
Use GAFeatureSelectionCV from sklearn-genetic-opt to find the optimal feature subset using evolutionary algorithms: capturing feature interactions that filter methods miss and automatically determining how many features to keep.
ReadApr 2026 · Data Systems
Build a real-time anomaly detection pipeline that consumes Apache Kafka streams and scores events with a scikit-learn model: complete with producer, consumer, and Docker Compose setup.
Read
Mar 2026 · MLOps
Wrap a trained scikit-learn model in a FastAPI REST endpoint, containerize it with Docker, and serve predictions at scale: a complete MLOps deployment template with a working GitHub repository.
ReadMar 2026 · Machine Learning
Compare grid search, random search, and evolutionary algorithms for hyperparameter optimization with sklearn-genetic-opt.
ReadFeb 2026 · Machine Learning
Hyperparameter tuning with GASearchCV from sklearn-genetic-opt using evolutionary algorithms.
ReadFeb 2026 · MLOps
Use MLflow to track experiments, compare runs, version models in the Model Registry, and promote the best model to production: all without losing reproducibility.
ReadJan 2026 · LLMs & Agents
Build a Retrieval-Augmented Generation system with LangChain, ChromaDB, and OpenAI. Cover document indexing, MMR-based retrieval, evaluation with RAGAS, and production optimizations like re-ranking and semantic caching.
ReadJan 2026 · Operations Research
Model the minimum headcount required to meet demand using pyworkforce: solving the workforce planning problem that operations teams face in call centers and shift-based industries.
ReadI design and build critical systems end to end: architecture, data, models, and product. If that is the scale you are working at, let us talk.