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Google DeepMind: Build Your Own Small Language Model
4.8(24)339 studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate Google DeepMind course explores the machine learning development pipeline through the lens of language modeling. Learners compare traditional n-gram models with modern transformer architectures, gaining hands-on experience building language models while examining responsible deployment in community contexts.
Who It's For
Aspiring research engineers and data practitioners who want to build language models from scratch and understand the end-to-end ML development pipeline.
Key Takeaways
- Language Model Evolution: Compare the strengths, limitations, and mechanics of n-gram models versus transformer architectures.
- Practical Coding Labs: Implement models to generate text, recognize language patterns, and explore internal model mechanics.
- Research Engineering & Ethics: Gain insight into research workflows and learn to address community challenges responsibly using machine learning.
About this course
In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
Price
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