Mind Over Data - The One Thing You Know and Machines Don't
Explore the intersection of human intuition and machine learning in causal reasoning, examining Bayesian networks, confounding factors, and real-world applications in AI and data analysis.
Federated Heavy Hitters Discovery with Differential Privacy
Explore federated learning, differential privacy, and heavy hitters discovery in this talk by Peter Kairouz. Learn about multiparty computation, open research, and practical applications in data analysis.
K-Means and K-Medians Under Dimension Reduction
Explore k-means and k-medians clustering algorithms under dimension reduction, examining distortion graphs, cost analysis, and combinatorial lemmas for robust high-dimensional statistics.
Practical AI Solutions Within Healthcare and Biotechnology - Michael Segala
Explore AI applications in healthcare, including image analysis, NLP, and time-series data. Learn about challenges, workflows, and real-world use cases in diagnostics and patient care.
ODSC West 2015 - Hacking Machine Data
Explore techniques for analyzing machine data, including Hidden Markov Models and anomaly detection. Learn to handle time-series datasets with high volatility and noise, applying real-world methods to extract valuable insights.
Using Free Text for Predictive Modeling
Explore efficient text representation for predictive analytics, covering techniques to transform varied-length text into fixed-length vectors for machine learning applications like sentiment analysis and news classification.
Buy or Wait? How the Bunny Predicts When to Buy Your Plane Ticket
Discover how to save on airfare using data-driven predictions. Learn about price fluctuations, optimal buying times, and strategies to secure the best deals for your travel plans.
Machine Learning: From ABCs to DEFs
Explore machine learning fundamentals, from basic concepts to practical applications, focusing on people, data, and code. Learn to build simple AI models and understand key ML principles.
ChatGPT and Excel Basics for Beginners
Learn to leverage ChatGPT for enhancing Excel skills, from basic to advanced tasks. Explore AI-powered solutions, ask effective questions, and improve your data handling capabilities.
HPC+AI-Enabled Real-Time Coherent X-ray Diffraction Imaging - IPAM at UCLA
Explore HPC and AI-enabled real-time coherent X-ray diffraction imaging, revolutionizing materials characterization with advanced light sources, multi-modal techniques, and innovative data processing methodologies.
Katharine Turner - PCA of Persistent Homology Rank Functions with Case Studies
Explore persistent homology rank functions through PCA, featuring case studies and insights into topological data analysis techniques.
Tensors in Statistics and Data Analysis
Explore tensors in statistics and data analysis, covering probability tensors, biological measurements, and signature tensors for time-series data. Learn about decompositions and algebraic properties in this comprehensive overview.
Machine Learning and Game Theory for Social Impact
Explore machine learning and game theory applications in security, sustainability, and food rescue, featuring real-world deployments and innovative solutions for societal challenges.
Methods for Scalable Probabilistic Inference - IPAM at UCLA
Explore scalable probabilistic inference methods for astrophysics, focusing on Gaussian Processes for time series analysis and open-source tools to accelerate Bayesian inference with large datasets.
Towards Assurance-Based Learning-Enabled Cyber-Physical Systems
Exploring formal verification, monitoring, and safety case formalization for assurance-based learning-enabled cyber-physical systems, focusing on autonomous vehicles and their complex components.
K-Means Clustering in Machine Learning and Neural Networks - Day 8
Explore K-Means Clustering algorithm for unsupervised learning, understanding its principles and applications in machine learning and neural networks.
Machine Learning and Neural Networks: Simple and Multiple Linear Regression - Day 5
Learn simple and multiple linear regression techniques for machine learning and neural networks, covering key concepts and practical applications.
Machine Learning at Amazon by Rajeev Rastogi
Explore machine learning applications at Amazon, from product recommendations to size prediction, with insights on challenges and innovative approaches in e-commerce AI.
ProtoDash - Fast Interpretable Prototype Selection by Karthik Gurumoorthy
Explore ProtoDash, a fast interpretable prototype selection method for extracting compact representations of large datasets, with applications in causal reasoning, data relationships, and prediction accuracy improvement.
Intelligence in Marketing - Real or Artificial?
Explore AI and Customer Intelligence for enhanced customer engagement and discover the future of marketing. Learn about market orientation, qualitative data, and the impact of COVID-19 on marketing strategies.
Always Know What to Expect From Your Data With Great Expectations
Learn to validate, test, and document data quality using great_expectations. Covers installation, initialization, context, demos with various datasets, and practical applications for data teams.