newsletterAugust 6, 2026·Towards Data Science

Last Month’s Machine Learning Lessons Learned

The downside of conference travel The post Last Month’s Machine Learning Lessons Learned appeared first on Towards Data Science.

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I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.

A step-by-step guide to building a data agent and conversational interface that let business users to explore data in natural language without SQL The post I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How. appeared first on Towards Data Science.

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I Built a Tool-Calling Agent in Python. Here’s How I Debugged It

A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post I Built a Tool-Calling Agent in Python. Here’s How I Debugged It appeared first on Towards Data Science.

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Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer

Enterprise Document Intelligence [Vol.1 #11] - When the first answer points elsewhere in the document, the pipeline loops back to fetch the linked context The post Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer appeared first on Towards Data Sc

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Introduction to Semi-Supervised Learning

A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data. The post Introduction to Semi-Supervised Learning appeared first on Towards Data Science.

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Last Month’s Machine Learning Lessons Learned

Key Takeaways

Related Articles

I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.

I Built a Tool-Calling Agent in Python. Here’s How I Debugged It

Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer

Introduction to Semi-Supervised Learning

Discussion

Last Month’s Machine Learning Lessons Learned

Key Takeaways

Related Articles

I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.

I Built a Tool-Calling Agent in Python. Here’s How I Debugged It

Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer

Introduction to Semi-Supervised Learning

Discussion

Related Articles

Towards Data Science
I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.
A step-by-step guide to building a data agent and conversational interface that let business users to explore data in natural language without SQL The post I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How. appeared first on Towards Data Science.

Towards Data Science
I Built a Tool-Calling Agent in Python. Here’s How I Debugged It
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post I Built a Tool-Calling Agent in Python. Here’s How I Debugged It appeared first on Towards Data Science.

Towards Data Science
Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer
Enterprise Document Intelligence [Vol.1 #11] - When the first answer points elsewhere in the document, the pipeline loops back to fetch the linked context The post Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer appeared first on Towards Data Sc

Towards Data Science
Introduction to Semi-Supervised Learning
A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data. The post Introduction to Semi-Supervised Learning appeared first on Towards Data Science.