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Explore multidimensional considerations in AI development beyond technical feasibility. Learn to integrate cultural, social, political, and legal aspects throughout the product lifecycle for more purposeful and impactful AI tools.
Explore AI-assisted creative writing for theater, covering LLM training, data preprocessing, and collaborative script generation. Learn about challenges and techniques in NLP for theatrical performances.
Structure ML projects using Clean Architecture to reduce technical debt. Learn actionable software engineering principles for data-intensive applications and manage project changes effectively.
Explore strategies for accurate and scalable offer categorization in e-commerce, addressing challenges, leveraging automation, and improving search relevance and product sorting.
Explore Topological Data Analysis (TDA) and its intersection with machine learning to enhance neural networks' geometric reasoning abilities across various applications.
Explore cross-modal transfer for protest detection using vision and language data. Learn how to leverage pretrained models for zero-shot event detection across different modalities.
Discover how to build a quality data warehouse using open-source tools. Learn about modern data stack architecture, test-driven approaches, and software development best practices for data transformation.
Explore a two-year data science program designed for higher vocational education, featuring industry-aligned courses and modern educational approaches like Discord communities and GitHub portfolios.
Explore AI-powered secure interpretation systems for healthcare, addressing language barriers and privacy concerns. Learn about challenges in developing inclusive NLP and speech technology for diverse environments.
Explore federated machine learning for privacy-preserving data analysis in production environments. Learn core concepts, features, and real-world use cases for regulated datasets in distributed settings.
Explore deep learning's role in autonomous driving software, addressing challenges and research in reducing traffic fatalities through AI-driven solutions.
Explore synthetic data generation for computer vision tasks when labeled data is scarce. Learn tools and approaches to build effective models using primarily synthetic data.
Explore vision-based activity detection for in-vehicle safety, covering data collection, algorithm development, and SoC integration. Learn to create robust systems for monitoring driver behavior and reducing distraction-related accidents.
Explore p-tuning, a prompt-learning method for adapting LLMs to low-resource languages. Learn to enhance NLP task performance using NVIDIA NeMo's continuous multitask learning of virtual prompts.
Explore an innovative cross-disciplinary approach to address ethical challenges in AI language models, focusing on data representation, fairness, and responsible innovation.
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