
Overview of Fast Data systems, their deployment on Mesos and DC/OS, and their impact on Big Data processing. Learn about the evolving landscape of data pipelines and efficient operational strategies.

Explore innovative protein design using deep learning and musical representations, bridging materials science and artificial intelligence for groundbreaking bioengineering applications.

Explore advanced statistical inference techniques for distributed and constrained environments, focusing on lower bound analysis and practical applications in complex data scenarios.

Explore the connection between private classification and online prediction, examining theoretical implications and potential applications in machine learning and data privacy.

Explore strategies to combat viral misinformation, focusing on vaccine skepticism and its impact on public health. Learn how data and technology can track and counter the spread of falsehoods.

Explore emerging tools like satellite imagery and analytics that reveal complex relationships between people and the planet, enabling new approaches to planetary health and social wellbeing.

Explore nonlinear spectral decompositions in imaging and inverse problems, focusing on variational theory and applications in data science, with computational methods discussed.

Applied mathematicians share their journeys to entrepreneurship, offering insights on career paths, challenges, and advice for aspiring math entrepreneurs in various industries.

Lightning Network channels: costs, optimization, and network structure implications. Explores conditions for channel establishment, cost formulas, and potential centralization in bitcoin payment networks.

Expert panel discusses strategies for Ph.D. success and post-doctoral career paths in academia, industry, and research labs, offering valuable insights for data mining doctoral students.

Explore how data science at HBCUs drives innovation, with insights from Talitha M. Washington on leveraging this field to advance research and create opportunities in STEM.

Explore statistical methods for identifying irregularities in election data, focusing on the 2020 US presidential race and its unique challenges in data analysis and interpretation.

Explore cutting-edge techniques for large-scale biomedical data sharing and analysis, addressing challenges and opportunities in this rapidly evolving field of computational biology and mathematics.

Explore the significance of small data in statistical and data science, emphasizing its role alongside big data in modern research and analysis methodologies.

Learn to monitor and evaluate ML models with Evidently AI, an open-source Python library for data scientists. Explore reports, test suites, and dashboards for continuous model quality assessment.

Comprehensive tutorial covering Google Sheets essentials: navigation, formulas, data manipulation, charts, pivot tables, functions, collaboration, and more. Perfect for beginners and intermediate users seeking to enhance spreadsheet skills.

Learn effective data storytelling techniques to enhance data analysis impact. Discover how to use visualizations, narratives, and creative approaches to make insights more relatable and actionable for businesses.

Learn effective data storytelling techniques to transform raw information into compelling narratives. Discover how to analyze, visualize, and communicate insights for evidence-informed decision-making in organizations.

Discover a tool-agnostic framework for effective data handling, emphasizing process over tools. Learn to adapt to new technologies and understand the importance of data literacy in today's changing landscape.

Learn time series analysis using KNIME: preprocessing, alignment, imputation, forecasting, and evaluation. Build a demand prediction application with (S)ARIMA and machine learning models through hands-on, codeless examples.

Explore methodologies for automating supervised machine learning pipelines, covering data cleaning, feature engineering, and model development. Gain insights from experienced data scientists on best practices and techniques.