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Google DeepMind: Discover The Transformer Architecture
4.8(19)138 studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate Google DeepMind course demystifies the inner workings of the transformer architecture. Through hands-on activities, learners dissect prompt processing, visualize attention weights, and explore multi-head and masked attention while learning community-centered AI design practices.
Who It's For
Data scientists, ML engineers, and researchers wanting a deep mechanical understanding of transformer architectures and attention mechanisms.
Key Takeaways
- Transformer Mechanics: Understand next-token prediction, prompt processing, and essential language model network components.
- Attention Mechanisms: Explore and visualize attention weights, masked attention, and multi-head attention in interactive exercises.
- Ethical AI Design: Apply stakeholder mapping, community values alignment, and participatory methods to AI projects.
About this course
In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.
Price
Free
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