2 dépôts
Awesome GitHub RepositoriesSystem Monitoring and Scaling
Techniques for distributed training and monitoring data distribution shifts in production.
Distinct from Distributed and Scaling Strategies: Combines training scale with production monitoring, whereas the parent is focused on scaling strategies.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · System Monitoring and Scaling. Refine with filters or upvote what's useful.
Awesome System Monitoring and Scaling GitHub Repositories
Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
- alirezadir/machine-learning-interviews
alirezadir/Machine-Learning-Interviews
8,455Voir sur GitHubThis project is a comprehensive machine learning interview guide and technical study resource designed for individuals preparing for machine learning and AI engineering roles. It provides a collection of materials and practice problems covering core algorithms, theoretical fundamentals, and the implementation of neural network architectures. The resource serves as a technical reference for generative AI development, focusing on the design and optimization of large language models and diffusion systems. It includes frameworks for system design, covering the architecture of production machine l
Includes guidelines on implementing distributed training and detecting data distribution shifts.
Jupyter Notebookagenticaiai-agents - subhashchy/the-accidental-cto
subhashchy/The-Accidental-CTO
3,168Voir sur GitHubThe Accidental CTO is a comprehensive collection of guides and frameworks focused on distributed systems architecture, resilience engineering, and system observability. It provides strategies for scaling applications from thousands to millions of users while maintaining high availability. The project offers specific methodologies for managing data volume through replication, sharding, and caching. It includes a framework for analyzing cloud infrastructure spending and evaluating transitions to self-hosted environments to reduce operational expenses. The resource covers the implementation of
Provides methodologies for growing user capacity using replication, sharding, and caching strategies.
TypeScriptscalingsystem-design
