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Data engineering for AI

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.

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Structured Data Extraction from Text with LLMs
LLMs & Agents
New
Structured Data Extraction from Text with LLMs
Jun 2026

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.

Python
LLMs
Pydantic
AI Agents with LangGraph for Data Analysis
LLMs & Agents
New
AI Agents with LangGraph for Data Analysis
Jun 2026

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.

LangGraph
LangChain
Python
Orchestrate ML Pipelines with Prefect
MLOps
New
Orchestrate ML Pipelines with Prefect
Jun 2026

Go from fragile training scripts to robust, observable ML workflows using Prefect. Schedule retraining, handle failures gracefully, and monitor every run.

Prefect
Python
MLOps
ML Model Monitoring in Production with Evidently
MLOps
New
ML Model Monitoring in Production with Evidently
Jun 2026

Learn how to detect data drift and model degradation in production using Evidently AI. Build automated reports and alerts before your model silently fails.

Evidently
Python
MLOps
Your First Machine Learning Model with Scikit-learn
Machine Learning
New
Your First Machine Learning Model with Scikit-learn
May 2026

A step-by-step guide to building your first ML model: data exploration, preprocessing, cross-validation, hyperparameter tuning, and evaluation — all with scikit-learn.

Python
scikit-learn
machine learning
Operations Research
Operations Research
How to Solve Scheduling Problems in Python
May 2026

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.

Python
pyworkforce
scheduling
Machine Learning
Machine Learning
Adaptive Parameters Methods for Machine Learning
Apr 2026

Explore how to use ExponentialAdapter and InverseAdapter in sklearn-genetic-opt to dynamically adjust mutation and crossover probabilities.

sklearn-genetic-opt
Python
adaptive parameters
Machine Learning
Machine Learning
Evolutionary Feature Selection for Machine Learning
Apr 2026

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.

sklearn-genetic-opt
Python
scikit-learn
Data Systems
Data Systems
Real-Time Anomaly Detection with Apache Kafka and Python
Apr 2026

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.

Apache Kafka
Python
anomaly detection
Serve a Machine Learning Model with Sklearn, FastAPI and Docker
MLOps
Serve a Machine Learning Model with Sklearn, FastAPI and Docker
Mar 2026

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.

FastAPI
Docker
scikit-learn
Machine Learning
Machine Learning
Are You Still Using Grid Search for Hyperparameters Optimization?
Mar 2026

Compare grid search, random search, and evolutionary algorithms for hyperparameter optimization with sklearn-genetic-opt.

sklearn-genetic-opt
Python
scikit-learn
Machine Learning
Machine Learning
Tune Your Scikit-learn Model Using Evolutionary Algorithms
Feb 2026

Hyperparameter tuning with GASearchCV from sklearn-genetic-opt using evolutionary algorithms.

sklearn-genetic-opt
Python
scikit-learn
MLOps
MLOps
Manage Your Machine Learning Lifecycle with MLflow in Python
Feb 2026

Use MLflow to track experiments, compare runs, version models in the Model Registry, and promote the best model to production — all without losing reproducibility.

MLflow
Python
MLOps
How to Build a RAG System with LangChain and Python
LLMs & Agents
How to Build a RAG System with LangChain and Python
Jan 2026

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.

RAG
LangChain
Python
Operations Research
Operations Research
Workforce Planning Optimization Using Python
Jan 2026

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.

Python
pyworkforce
OR-Tools
Building an AI or data platform?

Products, platforms, and open-source software for AI, Data Engineering, and Machine Learning.

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Vision

Building an ecosystem of products and open-source software for AI, Data Engineering, and Machine Learning.

Projects
sklearn-genetic-optPyWorkforceCiaren

Iterixs (Currently building)

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