newsletterJuly 13, 2026·Towards Data Science

Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything around them did. The post Building Models in Two Worlds: From Latent Constructs to Behavioral Signals appeared first on Towards Data Science.

Key Takeaways

•My PhD models tried to explain why people engage
•This story was reported by Towards Data Science, covering developments in the newsletter space.
•AI advancements continue to reshape industries — read the full article on Towards Data Science for complete coverage.

📖 Continue reading the full article:

Read Full Article on Towards Data Science →

Share this article

X Facebook Reddit ☕ Support

Towards Data Science

Agentic RAG: Let the Agent Search

A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science.

Towards Data Science

Context Rot: Why Claude Code Sessions Decay, and How to Govern Them

Long sessions rot quietly, well before any token limit is reached. Here’s why, and how to govern your context in Claude Code. The post Context Rot: Why Claude Code Sessions Decay, and How to Govern Them appeared first on Towards Data Science.

Towards Data Science

The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices

A framework for aligning agentic AI with enterprise intent to ensure consistent scenario‑wide autonomous behavior. The post The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices appeared first on Towards Data Science.

Towards Data Science

RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each

Two techniques, two different problems, and why the question is not really "which one wins" The post RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each appeared first on Towards Data Science.

Discussion

Loading articles...

Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

Key Takeaways

Related Articles

Agentic RAG: Let the Agent Search

Context Rot: Why Claude Code Sessions Decay, and How to Govern Them

The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices

RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each

Discussion

Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

Key Takeaways

Related Articles

Agentic RAG: Let the Agent Search

Context Rot: Why Claude Code Sessions Decay, and How to Govern Them

The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices

RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each

Discussion

Related Articles

Towards Data Science
Agentic RAG: Let the Agent Search
A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science.

Towards Data Science
Context Rot: Why Claude Code Sessions Decay, and How to Govern Them
Long sessions rot quietly, well before any token limit is reached. Here’s why, and how to govern your context in Claude Code. The post Context Rot: Why Claude Code Sessions Decay, and How to Govern Them appeared first on Towards Data Science.

Towards Data Science
The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices
A framework for aligning agentic AI with enterprise intent to ensure consistent scenario‑wide autonomous behavior. The post The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices appeared first on Towards Data Science.

Towards Data Science
RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each
Two techniques, two different problems, and why the question is not really "which one wins" The post RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each appeared first on Towards Data Science.