Data Science
Data analysis, visualization, and engineering insights
// 5 articles filed
Data analysis, visualization, and engineering insights
// 5 articles filed
Great Expectations lets you define what good data looks like, validate it automatically in your pipeline, and generate documentation - catching data issues before they corrupt your models.
Mahmudul Haque Qudrati
CEO & ML Engineer
dbt (data build tool) lets analysts transform data in the warehouse using SELECT statements, with built-in testing, documentation, and dependency tracking - no more unmaintainable SQL scripts.
Mahmudul Haque Qudrati
CEO & ML Engineer
Pandas 2.x introduces Copy-on-Write semantics by default and a PyArrow memory backend that uses 10x less memory on string columns - here is what changed and how to migrate.
Mahmudul Haque Qudrati
CEO & ML Engineer
DuckDB runs inside your Python or R process with zero setup, queries Parquet files directly with SQL, and outperforms Spark on datasets under 100GB on a single machine.
Mahmudul Haque Qudrati
CEO & ML Engineer
Polars is a blazing-fast DataFrame library built in Rust that outperforms Pandas by 10-100x on large datasets, with lazy evaluation and parallel execution built in.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deep dives into ML algorithms, models, and applications
AI trends, techniques, and real-world implementations
How LLMs work, honest comparisons, and production usage
Every technique that works — with real examples
Claude Code, Cursor, Copilot, open-source tools reviewed honestly
Local LLMs, open models, free AI infrastructure
Fewer tokens, cheaper APIs, local alternatives with real numbers
Benchmarks explained, evaluation frameworks, model testing
LLM SEO, AI SEO, Google AI Overviews, developer marketing
iOS, Android, and cross-platform mobile app development
Modern web technologies, frameworks, and best practices
Autonomous agents, LLM applications, and intelligent systems