Production patterns for AI agents, RAG pipelines, data infrastructure, and MLOps. No theory-only posts — every article comes from a real deployment.
Kafka producer and consumer best practices for `acks`, idempotence, retries, offsets, commits, partitioning, and error handling in production streaming systems.
Learn Kafka topic and partition strategy for scalability, consumer parallelism, ordering guarantees, throughput planning, and long-term cluster design.
Five practical ways teams still use logistic regression, and why this classic model remains valuable even in a deep learning era.
A practical introduction to Apache Flink and where it fits in modern stream-processing and event-driven data systems.
A practical guide to sentiment analysis comparing Naive Bayes and LSTM, and how teams should think about modern sentiment-analysis pipelines today.
A practical machine learning mind map covering ML tasks, methods, model families, and application areas for a clearer overview of the field.
A practical guide to the most relevant Google AI tools for modern teams, including Gemini, Vertex AI, Agent Builder, search, vision, and MLOps workflows.
A practical overview of Kubernetes, what it manages, and when it is the right operational layer for containerized systems.
A practical overview of data science in HR, covering eight high-value use cases for hiring, retention, workforce planning, performance insight, and people operations.
A practical introduction to Docker, containers, images, and the kinds of problems Docker actually solves in modern software delivery.
Compare ScyllaDB and Apache Cassandra on performance, latency, hardware efficiency, operational tradeoffs, and migration fit for distributed NoSQL workloads.
A practical guide to NLP algorithms and concepts, covering common NLP tasks, classical models, embeddings, transformers, retrieval, and modern natural language processing workflows.