newsletterAugust 12, 2026·Towards Data Science

How to Place Vertiport Locations in Any City Using Geospatial Machine Learning

A reproducible Lagos case study with population data, transport access, and airspace constraints The post How to Place Vertiport Locations in Any City Using Geospatial Machine Learning appeared first on Towards Data Science.

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•A reproducible Lagos case study with population data, transport access, and airspace constraints The post How to Place Vertiport Locations in Any City Using Geospatial Machine Learning appeared first on Towards Data Science.
•This story was reported by Towards Data Science, covering developments in the newsletter space.
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Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From

Enterprise Document Intelligence [Vol.1 #5nonies] - Nature, plan, execute, synthesize: closing brick 1 with a dispatcher that reads each PDF’s nature and picks the method that fits, fitz, Docling, PaddleOCR, EasyOCR, MinerU or Surya, then folds the outputs into one corpus The post Before Full Agenti

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Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works

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Building Multimodal Workflows with a Local LLM

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Stop Calling the First Significant Day a Win

Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost 28 percent. I use a seeded simulation to show how large the damage gets and compare the fixes that keep early stopping honest. The post Stop Calling the First Significant Day a Win appeared fi

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How to Place Vertiport Locations in Any City Using Geospatial Machine Learning

Key Takeaways

Related Articles

Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From

Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works

Building Multimodal Workflows with a Local LLM

Stop Calling the First Significant Day a Win

Discussion

How to Place Vertiport Locations in Any City Using Geospatial Machine Learning

Key Takeaways

Related Articles

Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From

Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works

Building Multimodal Workflows with a Local LLM

Stop Calling the First Significant Day a Win

Discussion

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Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From
Enterprise Document Intelligence [Vol.1 #5nonies] - Nature, plan, execute, synthesize: closing brick 1 with a dispatcher that reads each PDF’s nature and picks the method that fits, fitz, Docling, PaddleOCR, EasyOCR, MinerU or Surya, then folds the outputs into one corpus The post Before Full Agenti

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Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works
From one gradient to every gradient The post Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works appeared first on Towards Data Science.

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Building Multimodal Workflows with a Local LLM
Image inputs and structured outputs with Gemma 4 and Ollama The post Building Multimodal Workflows with a Local LLM appeared first on Towards Data Science.

Towards Data Science
Stop Calling the First Significant Day a Win
Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost 28 percent. I use a seeded simulation to show how large the damage gets and compare the fixes that keep early stopping honest. The post Stop Calling the First Significant Day a Win appeared fi