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Machine learning at scale
Machine learning at scale: Learn about ML systems from top tech companies. Delivered once a week in your inbox.
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Why choose Machine learning at scale?
Core Summary
Machine learning at scale is a subscription-based knowledge platform dedicated to helping Machine Learning engineers upskill, with the goal of making them a x10 Machine Learning Engineer. The platform is run by Ludovico Bessi (Ludo), a Machine Learning engineer at Google, and is already subscribed to by over 6000 Machine Learning engineers from leading companies like Google, Amazon, YouTube, and Microsoft.
Main Content & Features
- Anatomy of ML Systems: Deep dive into the internal structure and components of machine learning systems.
- Patterns of ML Systems: Explore common patterns and best practices in ML system design.
- ML Systems Case Studies: Analyze the construction and optimization of large-scale ML systems through real-world cases.
Upcoming Deep Dives
- LLM training: Large Language Model training.
- LLM Inference At Scale: Large-scale LLM inference.
- Recommendation Systems at Scale: Large-scale recommendation systems.
- Computer Vision Systems in Production: CV systems in production environments.
- Search & Ranking Systems: Search and ranking systems.
- MLSys course: Machine Learning Systems course.
Target Users
- Machine Learning engineers looking to upskill and unlock their full potential.
- Businesses looking for AI help, specifically in Retrieval, Ranking, Recommendation systems, and LLM integrations.
Core Advantages & Author Background
Content is provided by an expert with rich frontline practical experience. Ludovico Bessi's key achievements include:
- Worked with large scale ML systems to fight abuse across billions of users at 500k QPS at Google.
- Pretrained and finetuned transformer-based models to understand user behaviour.
- Working with the end-to-end YouTube Ads systems from Ads selection to formats.
- Making YouTube the best video shopping destination on the planet by building better Recommendation systems.
- Applied Machine Learning techniques at CERN to understand particle interactions.
- Developed computer vision thesis based on Transformers at Volvo.
Usage & Pricing
- Users can subscribe via Substack to get weekly high-quality insights, currently offered for free.
- Businesses seeking AI help (specializing in Retrieval, Ranking, Recommendation systems, and LLM integrations) can reach out via LinkedIn for a free initial consultation.
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