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Explore how data science transforms social media data, revealing insights to optimize profits for high-revenue properties. Learn about AI model building, applications, failures, bias, and solutions.
Learn best practices for building ML data labeling pipelines through crowdsourcing. Explore real-life examples, requirements, and techniques for high-quality labeled data in supervised machine learning projects.
Explore vision transformers' architecture, self-attention in computer vision, and applications in recognition, segmentation, and multi-modal learning. Discover their potential for general-purpose model architectures.
Explore AI's impact on cybersecurity, its potential risks and benefits, and strategies for ensuring AI safety and ethical development in this thought-provoking talk by Dr. Yampolskiy.
Learn to build robust data pipelines using dbt, Airflow, and Great Expectations. Discover how these tools complement each other to ensure data quality, perform transformations, and orchestrate workflows effectively.
Explore responsible AI use in healthcare, addressing challenges, identifying biases, and implementing ethical practices to enhance patient outcomes and promote health equity.
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.
Explore deep learning survival analysis for precise credit risk prediction in consumer lending, combining traditional methods with advanced techniques for improved time-to-event forecasting.
Explore Bloomberg's AI-driven search and discovery system for financial news, leveraging machine learning and NLP to parse unstructured data and provide valuable insights for clients.
Discover how quantization in PyTorch can make AI models lighter, faster, and more power-efficient without compromising accuracy. Learn techniques and workflows from an ML expert at Meta AI.
Explore how data science combats COVID-19 through mobility models, epidemiological predictions, and large-scale surveys. Learn key technical skills and insights from Dr. Nuria Oliver's multidisciplinary team of volunteer scientists.
Explore data-centric AI with Alex Ratner: operationalizing knowledge, managing training data, and leveraging foundational models for real-world applications in machine learning and responsible AI.
Explore challenges in AI and healthcare equity, focusing on race and ethnicity data. Learn about bias in algorithms and data, and discover opportunities for improving healthcare AI through better data and models.
Discover strategies for building efficient real-time data science systems. Learn about data movement, design patterns, and best practices for writing, testing, and reproducing analytics in real-time environments.
Explore social biases in text representations and their mitigation with NLP expert Danushka Bollegala. Learn about gender bias, word embeddings, masked language models, and multi-lingual bias evaluation in AI systems.
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