How to Use ChatGPT Like a Pro: 10 Workflows That Save You Hours Every Week
Do you also think ChatGPT is useless? If not, you must’ve come across someone who does. People who say “I didn’t find it useful”, or “it couldn’t do what I told it to”, or the classic “AI is senseless“. While such people think the tool is weak, the fact is that they fail because their […]
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The 4 statistical sins that invalidate most A/B tests, plus a pre-test checklist and Bayesian vs frequentist decision framework you can use Monday.
The post Why Most A/B Tests Are Lying to You appeared first on Towards Data Science.
I Stole a Wall Street Trick to Solve a Google Trends Data Problem
A methodology for comparing Google Trends data across countries.
The post I Stole a Wall Street Trick to Solve a Google Trends Data Problem appeared first on Towards Data Science.
Why Your AI Search Evaluation Is Probably Wrong (And How to Fix It)
A five-step framework for building rigorous, reproducible AI search benchmarks — before you make six-figure infrastructure decisions
The post Why Your AI Search Evaluation Is Probably Wrong (And How to Fix It) appeared first on Towards Data Science.
Write C Code Without Learning C: The Magic of PythoC
Compile native, standalone applications using the Python syntax you already know.
The post Write C Code Without Learning C: The Magic of PythoC appeared first on Towards Data Science.
Pyright Guide: Installation, Configuration, and Use Cases
Have you ever wanted faster type checking for Python without slowing down your workflow? Tools like MyPy can catch type errors, but they often feel slow or disconnected from the editor experience. This is where Pyright comes in. Pyright is a standards-based static type checker for Python designed fo...
Understanding Context and Contextual Retrieval in RAG
Why traditional RAG loses context and how contextual retrieval dramatically improves retrieval accuracy
The post Understanding Context and Contextual Retrieval in RAG appeared first on Towards Data Science.
Sarvam Edge: A Beginner’s Guide to On-Device AI for India
Suppose there is a smart computer in your cell phone. It responds instantly, knows your language, and is completely functional even without the internet. This AI will keep your information confidential on your device. It does not need any additional charge per question. Such is the future that Sarva...
The Data Team’s Survival Guide for the Next Era of Data
6 pillars to declutter your stack, escape the service trap, and build the missing foundations for the new primary data consumer: the AI agent.
The post The Data Team’s Survival Guide for the Next Era of Data appeared first on Towards Data Science.
The Black Box Problem: Why AI-Generated Code Stops Being Maintainable
Same notification system, two architectures. Unstructured generation couples everything into a single module. Structured generation decomposes into independent components with explicit, one-directional dependencies. Image by the author
The post The Black Box Problem: Why AI-Generated Code Stops Bein...
How to Create Production-Ready Code with Claude Code
Learn how to write robust code with coding agents.
The post How to Create Production-Ready Code with Claude Code appeared first on Towards Data Science.
Learn how Zero Redundancy Optimizer works, how to implement it from scratch, and how to use it in PyTorch
The post AI in Multiple GPUs: ZeRO & FSDP appeared first on Towards Data Science.
An overview of powerful methods for transforming continuous variables into discrete ones
The post 5 Ways to Implement Variable Discretization appeared first on Towards Data Science.
Time Series Cross-Validation: A Guide to Techniques & Practical Implementation
Time series data drives forecasting in finance, retail, healthcare, and energy. Unlike typical machine learning problems, it must preserve chronological order. Ignoring this structure leads to data leakage and misleading performance estimates, making model evaluation unreliable. Time series cross-va...
A Guide to Kedro: Your Production-Ready Data Science Toolbox
This article introduces and explores Kedro's main features, guiding you through its core concepts for a better understanding before diving deeper into this framework for addressing real data science projects.