From manual voter registration to real-time results, Steve Adeshina used tech to transform Nigeria's elections. Discover how he made it happen.

Learn how Grab is modernising its machine learning platform with a feature table-centric architecture powered by AWS Aurora for Postgres. This shift from a legacy feature fetching system to…

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In this video, I show you how to use LangExtract to generate high-quality metadata for your Retrieval Augmented Generation (RAG) system. By extracting structured data from unstructured documents, we can filter results more effectively and drastically improve…

Embrace your inner software developer The post Reducing Time to Value for Data Science Projects: Part 4 appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to the original author. Source

In the early days of large language models (LLMs) like GPT-3, prompt engineering emerged as the most popular and sought after skill. By carefully crafting instructions, users could elicit intelligent responses from models with limited memory and no real-world…

Grab has embarked on a transformative journey to overhaul its enterprise data ecosystem, addressing challenges posed by the rapid growth of its business spanning across ride-hailing, food delivery, and financial services. With the increasing complexity of…

Part 2: Prompt Engineering for Features, Modeling, and Evaluation The post Advanced Prompt Engineering for Data Science Projects appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to the original author. Source

Facing setbacks and soaring costs, Nigerian students learn resilience in their drone project. How did they adapt and overcome challenges?

How are African students overcoming hardware access challenges to innovate in engineering? Discover the creative solutions emerging across the continent.