Turning Membership Surveys Into Action - Predictive Analytics
Learn to transform membership survey data into actionable insights using factor analysis and predictive modeling techniques for more effective decision-making and stakeholder engagement.
Train Your Swift - Computational Statistics in Swift Examples
Explore statistical models, bag-of-words classification, and Markov Chain algorithms in Swift. Learn to implement mathematical concepts for sorting, classifying, and generating data through practical examples.
Regression Using Neural Networks and Comparison to Other Models
Explore neural network regression, compare with other models, and learn practical implementation using Python for data analysis and prediction.
Instrumental Variable Estimation: STATA Application of IV Using 2SLS - Part 9
Apply instrumental variable estimation using two-stage least squares in STATA, enhancing your econometric analysis skills with practical implementation.
Excel Statistical Analysis - Introduction
Explore Excel's statistical analysis tools for business applications in this comprehensive introduction to Highline College's Busn 210 course.
Container Tracking and Demand Forecasting for Bosch Tools Supply Chain Operations
Discover how BOSCH Power Tools leverages neural forecasting models in AWS cloud to optimize demand forecasting, reduce inventory costs, and enhance supply chain stability for millions of product time series.
Hierarchical Forecasting in Python - Introduction to the Hierarchical Forecast Library
Explore open-source Hierarchical Forecast library for time series datasets, featuring reconciliation algorithms, preprocessed data, evaluation metrics, and statistical baseline models.
Building a User-Level Targeting Platform for Personalized Coupon Offers
Explore innovative coupon targeting techniques using HTE models for personalized offers. Learn about statistical methods and efficient data processing for real-time responses in this cutting-edge platform.
Granger Causal Model: Introduction and Application in Regression Analysis
Explore the Granger Causal model, an application of regression that attempts to address causality in data analysis beyond mere correlation.
Handling Multicollinearity with Ridge Regression in Python
Implement Ridge Regression using Python and sklearn to handle multicollinearity in data analysis.
Introduction to Logistic Regression
Learn about binary classification, logistic regression, and related concepts like probit and logit links in this concise introduction to fundamental statistical modeling techniques.
Implementing Linear Discriminant Analysis (LDA) with Irish Data Sets in R
Implement LDA using Irish datasets in R, gaining practical experience with Linear Discriminant Analysis techniques.
Gaussian Process Regression
Explore non-linear regression techniques, focusing on Gaussian Process Regression, basis functions, and systems. Gain insights into GP priors for advanced statistical modeling.
Hands-on R: Implementing Tree Regression and Random Forest with Simulated Data
Implement tree regression and random forest techniques using simulated data in R, gaining practical experience with these powerful machine learning algorithms.
Logistic Regression Implementation in R for Automotive Crash Testing
Implement logistic regression in R for automotive crash testing, from data preparation to model evaluation and prediction.
Predictive Modelling
Explore predictive modeling techniques and applications for data-driven decision-making and forecasting in various domains.
Hands-on with Python: Estimating Regression Coefficients with OLS and Abline - Part 2
Estimate regression coefficients using OLS and abline in Python, gaining practical experience with statistical analysis techniques.
Geometry of Regression Model and Feature Engineering
Explore regression model geometry and feature engineering techniques to enhance data analysis and model performance.
Nepal in the Loop - Human-Aided Decision Making in Machine Learning
Explore human-aided machine learning and its potential to empower Nepal's workforce in the global data economy, led by an experienced data scientist.
Probabilistic Flow Circuits: Towards Deep Models for Tractable Inference - Oral Session 6
Explore a novel approach combining probabilistic circuits with normalizing flows for enhanced expressivity while maintaining tractable inference in deep probabilistic models.
Deep Symbolic Regression - Petersen et al.'s 2021 ICLR Paper
Explore deep symbolic regression through Petersen et al.'s 2021 ICLR paper, covering innovative techniques at the intersection of symbolic methods and deep learning.