Machine learning at scale
PaidBecome a x10 Machine Learning Engineer
About Machine learning at scale
Machine Learning at Scale is a Substack publication by Ludovico Bessi that delivers weekly insights on machine learning systems from top tech companies. It aims to help machine learning engineers upskill and become x10 engineers by providing high-quality content on topics like RAG systems, LLM optimizations, LLM training, and ML system design. The publication also features tools used by machine learning engineers and deep dives into specific topics.
How to Use
Subscribe to the Machine Learning at Scale Substack publication to receive weekly insights directly in your inbox. You can also access the archive of past articles on the website and explore resources like the YouTube channel and ML System design course (coming soon).
Machine Learning at Scale's
Key Features
- Weekly newsletter with high-quality insights
- Deep dives into ML topics
- Tools used by Machine Learning engineers
- ML System design course (coming soon)
- YouTube channel (coming soon)
- Archive of past articles
Use Cases
- Upskilling as a Machine Learning engineer
- Learning about ML systems at scale
- Staying updated on the latest ML tools and techniques
- Understanding ML system design principles
Key Features
Pros & Cons
- Content authored by an experienced Google ML engineer with real-world scale experience
- Free weekly insights with no paywall mentioned
- Covers a wide range of production ML topics (LLMs, recommendations, ads, search)
- Practical focus on case studies and design patterns
- Growing community of 10k+ ML engineers from leading companies
- Some promised content (MLSys course, YouTube channel) is still 'coming soon'
- Limited interactive or hands-on components; purely reading material
- No explicit mention of frequency or depth of newsletter issues