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Scaling AI Models with Mixture of Experts (MOE) Design Principles and Real-World A... - OneDDL - 10-22-2025
![[Image: a8f0c7df17ba2b1a39531ca1cc4058cf.webp]](https://i126.fastpic.org/big/2025/1022/cf/a8f0c7df17ba2b1a39531ca1cc4058cf.webp)
Free Download Scaling AI Models with Mixture of Experts (MOE) Design Principles and Real-World A...
Released 10/2025
With Vaibhava Lakshmi Ravideshik
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 55m 51s | Size: 232 MB
Get a hands-on overview of Mixture of Experts (MoE) architecture, covering key design principles, implementation strategies, and real-world applications in scalable AI systems.
Course details
Mixture of Experts (MoE) is a cutting-edge neural network architecture that enables efficient model scaling by routing inputs through a small subset of expert subnetworks. In this course, instructor Vaibhava Lakshmi Ravideshik explores the inner workings of MoE, from its core components to advanced routing strategies like top-k gating. The course balances theoretical understanding with hands-on coding using PyTorch to implement a simplified MoE layer. Along the way, you'll also get a chance to review real-world applications of MoE in state-of-the-art models like GPT-4 and Mixtral.
Homepage
https://www.linkedin.com/learning/scaling-ai-models-with-mixture-of-experts-moe-design-principles-and-real-world-applications
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