News

EPFL Researchers Introduce MEMOIR: A Scalable Framework for Lifelong Model Editing...

June 18

OpenAI may soon let you sign in to third-party apps with...

3 weeks ago

Anthropic rolls out a voice mode for its Claude chatbot apps

3 weeks ago

Research shows AI is already cutting entry-level jobs in tech

3 weeks ago

Xbox begins testing Copilot on mobile

3 weeks ago

Xbox begins testing Copilot on mobile

Here’s what it’ll take for Nvidia and other US chipmakers to...

3 weeks ago

Here’s what it’ll take for Nvidia and other US chipmakers to flog AI chips in China

The Oppo A5m retail listing reveals the specs and price of...

3 weeks ago

The Oppo A5m retail listing reveals the specs and price of this device

Geekbench database shows a Samsung Galaxy Tab S10 Lite

3 weeks ago

Geekbench database shows a Samsung Galaxy Tab S10 Lite

Apple’s new OS name could make the ‘iPhone 17″ sound even...

3 weeks ago

Apple’s new OS name could make the ‘iPhone 17″ sound even more bizarre

New Apple TV 4K is coming: Four features expected later this...

3 weeks ago

New Apple TV 4K is coming: Four features expected later this year

LLMs Can Now Reason Beyond Language: Researchers Introduce Soft Thinking to...

3 weeks ago

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Featured

Building High-Performance Financial Analytics Pipelines with Polars: Lazy Evaluation, Advanced Expressions,...

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Hugging Face partners with Groq for ultra-fast AI model inference

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Ren Zhengfei: China’s AI future and Huawei’s long game

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27 minutes ago

Building High-Performance Financial Analytics Pipelines with Polars: Lazy Evaluation, Advanced Expressions,...

In this tutorial, we delve into building an advanced data analytics pipeline using , a lightning-fast DataFrame library designed for optimal performance and scalability. Our goal is to demonstrate how we can utilize Polars’ lazy evaluation, complex expressions, window functions, and SQL interface to process large-scale financial datasets efficiently....