Introduction to Text Analytics with R - Pre-Processing Our Test Data
Learn to preprocess test data, cache IDF values, perform SVD projections, and evaluate model effectiveness for text analytics in R. Enhance your skills in handling unseen textual data and making predictions.
Intro to Big Data, Data Science & Predictive Analytics
Explore the diverse world of big data, data science, and predictive analytics. Gain insights into subfields, real-world applications, and the components of a big data pipeline across various industries.
Statistical Learning I - Foundations and Principles
Explore statistical learning fundamentals with Robert Schapire from Microsoft Research, covering key concepts and applications in machine learning and data analysis.
Dual-SPLS - A Versatile Approach Improving PLS with Lasso Shrinkage
Explore dual-sPLS, an innovative algorithm combining PLS and Lasso for improved variable selection and dimension reduction in high-dimensional analytical chemistry problems, offering enhanced accuracy and interpretability.
Advances in Predictive Models for Single-cell and Regulatory Genomics
Explore cutting-edge predictive models for single-cell and regulatory genomics, enhancing understanding of cancer progression and potential treatment approaches.
AI-Based Modeling of Electronic Health Records for Patients with Learning Disabilities
Explore AI-based modeling of electronic health records for individuals with learning disabilities, focusing on predicting hospital stays and analyzing long-term condition trajectories.
Can AI Save Our Planet? - Environmental Applications of Artificial Intelligence
Exploring AI's potential to address climate change through monitoring and predicting environmental responses, discussing challenges in applying these methods to our complex natural world.
Quantifying the Uncertainty in Model Predictions Using Conformal Prediction
Learn techniques for quantifying uncertainty in neural network predictions, focusing on conformal prediction as a versatile, statistically rigorous method applicable to classification and regression tasks.
Creating an ML Model as a Business User
Validate use cases, build models, and develop business cases for ML deployment as a non-technical user.
Data-Centric AI Approach in Pharmaceutical Industry - AstraZeneca Case Study
Explore data-centric AI in pharma: personalized doctor education, patient treatment optimization, and real-world data utilization for predictive modeling at AstraZeneca.
Introduction to Machine Learning with Python
Explore machine learning fundamentals using Python, covering key concepts and practical applications in this hands-on workshop led by a field engineer from Domino.
Retail AI Use Case: Building a Demand Prediction Model
Explore retail AI demand prediction models, KPIs, and implementation strategies for effective business use cases in the retail industry.
COVID-19 Vaccination Demand Forecasting in Canadian Pharmacies
Develop an analytic forecasting framework for COVID-19 vaccination demand in Canadian pharmacies using historical data, geospatial demographics, and digital surveys.
Statistical Rethinking 2022 - Multi-Multilevel Models
Explore advanced statistical concepts including multiple cluster types, multilevel predictions, and non-centered priors in this comprehensive lecture on multi-multilevel models.
Understanding Predictive Modeling with R
Learn to create predictive models using R, covering key concepts, training techniques, and practical demonstrations. Gain insights into model selection and explore various applications in data analysis.
Theory and Methods Challenges in Counterfactual Prediction - Karla Diaz-Ordaz
Explore causal inference in AI prediction, enhancing algorithms with 'what if' capabilities for decision-making and fairness. Learn about counterfactual prediction challenges and methodologies.
Enriching Latent Class Models With Counterfactual Prediction - Mark Gilthorpe
Exploring counterfactual prediction in AI: enhancing prediction algorithms with 'what if' capabilities for improved decision-making and fairness in healthcare, insurance, and beyond.
Chaos Theory and Geometry - Can They Predict Our World? With Tim Palmer
Explore chaos theory's geometry to predict uncertain phenomena like weather, pandemics, and quantum physics. Discover insights into the universe and ourselves through fractal patterns and probabilistic approaches.
Mathematics at the Roots: Empowering Agriculture with Artificial Intelligence
Explore how AI revolutionizes agriculture, enhancing crop yields and sustainability through data-driven insights and innovative mathematical models.
Linear Regression
Explore linear regression concepts, techniques, and applications for data analysis and predictive modeling.
Multiple Linear Regression
Explore multiple linear regression techniques for analyzing relationships between multiple variables and predicting outcomes in statistical modeling.