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Explore AI Singapore's Synergos system for federated learning, a privacy-preserving technique that trains models across decentralized parties without exchanging data, addressing privacy concerns and regulatory compliance.
Standardized workflow for building scalable AI computer vision applications, covering data preparation, annotation, model selection, benchmarking, deployment, and monitoring for efficient development.
Explore Bayesian statistical computation and Hamiltonian Monte Carlo algorithms using PyMC3, an open-source probabilistic programming package. Learn to apply these advanced techniques to complex models in Python.
Discover how to achieve GPU-level performance for deep learning inference using only software on commodity CPUs, challenging conventional wisdom and offering a cost-effective, flexible solution for scaling AI models.
Learn best practices for cloud migration using automated lineage. Discover how to scope projects, compare lineage paths, prevent privacy issues, and accelerate execution with hybrid cloud data warehouses.
Explore AI and ML techniques for extracting actionable insights from alternative data sources in finance, leading to profitable trading strategies and robust portfolio construction.
Explore how AI revolutionizes retail, enhancing customer experiences and streamlining operations. Learn about personalized shopping, data quality, and future trends in e-commerce.
Exploring the future of human-robot collaboration, addressing challenges in integrating robots into society, and discussing the societal impact of widespread robot deployment in various settings.
Explore advanced techniques for machine learning with limited labeled data, including domain adaptation, few-shot learning, and self-supervised learning to enhance model performance across diverse domains and novel categories.
Explore knowledge graphs' potential in enhancing machine learning, tackling misinformation, and addressing global challenges like climate change and COVID-19 through semantic web principles and real-world applications.
Explore event data modeling in cloud data warehouses, focusing on benefits, user journeys, and practical examples. Learn to create a single source of truth for data-driven business decisions.
Explore ethical considerations in data science, covering data collection, storage, analysis, and modeling. Learn practical strategies to address ethical challenges in your work.
Explore reinforcement learning for robotics, covering key concepts, workflow, and practical applications. Learn to define environments, create agents, and deploy policies to hardware platforms.
Explore bias in AI vision and language with Margaret Mitchell, focusing on ethical concerns, societal impacts, and strategies for developing more inclusive and fair artificial intelligence systems.
Explore a systems change approach for data science and AI solutions with Jake Porway, focusing on the Data for Good movement and leveraging technology for social impact.
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