AI

Grok Bot executes workflows autonomously using skills, routines, and plugins. This tutorial walks through building two practical automation bots step by step.

Traces the sigmoid function's origins from compound interest and Euler's number to its role as an activation function in neural networks.

Replace slow Python loops with efficient NumPy vectorized operations. Learn element-wise ops, boolean masking, broadcasting, and axis-based aggregation.

Survival analysis handles censored data that ordinary regression cannot. This guide covers Kaplan-Meier estimation and Cox proportional hazards regression in Py

Most AI agent pilots never reach production. These five tools address the critical layers that close the gap between a working prototype and a reliable system.

Build a local AI agent that watches Wikipedia's live edit feed and reasons about vandalism using a two-stage filtering pipeline and Ollama.

Seven asyncio patterns for coordinating concurrent AI agents in Python, with production-level trade-offs for each approach.

A constrained LP approach to budget allocation that preserves shadow prices, letting the model explain exactly what each rule costs.

Token costs compound non-linearly in agentic AI loops. Learn five failure modes and the architectural patterns to control them.

Compare Ollama, LM Studio, and llama.cpp across five key axes to find the right local AI runtime for your workflow.

Optimizing for predictive fit can bias treatment effect estimates. BAC and double machine learning offer principled fixes—with important caveats.

Active learning selects the most informative unlabeled samples for human annotation. This tutorial covers uncertainty sampling, diversity-based sampling, and qu