'Regression modeling' presentation slideshows

743 views • 51 slides

Tree Structured Prognostic Model for Hepatocellular Carcinoma

Tree Structured Prognostic Model for Hepatocellular Carcinoma. Taerim Lee (1) , Hyungjun Cho (2) , Hyosuck Lee (3) (1) Dept of Information Statistics Korea National Open University

565 views • 43 slides

Case-control studies

Case-control studies. Overview of different types of studies Review of general procedures Sampling of controls implications for measures of association implications for bias Logistic regression modeling. Learning Objectives.

583 views • 37 slides

Empirical Understanding of Traffic Data Influencing Roadway PM 2.5 Emission Estimate

Empirical Understanding of Traffic Data Influencing Roadway PM 2.5 Emission Estimate. NSF-UC 2012-2013 Academic-Year REU Program. GRA Mentors. Faculty Mentor. Undergraduate Researchers. Heng Wei, Ph.D., P.E. Associate Professor Director, ART-Engines Lab School of Advanced Structures

337 views • 27 slides

Understanding Foodborne Disease Outbreaks Using Environmental Assessments: The Importance of Antecedents to Contribu

Understanding Foodborne Disease Outbreaks Using Environmental Assessments: The Importance of Antecedents to Contributing Factors. Vincent J. Radke, MPH, RS, CP-FS, DAAS, CPH Sanitarian Centers for Disease Control and Prevention Sixth International Conference on Food Safety Dubai, 2011.

407 views • 21 slides

Six Sigma - the Latest Approach in the Ongoing Development of Strategies for Business Improvement

Six Sigma - the Latest Approach in the Ongoing Development of Strategies for Business Improvement. Use of analytical methods has grown steadily for over 80 years Statistical quality control (origins in 1920, explosive growth during WW II, 1950s) Operations research (1940s)

275 views • 15 slides

Six Sigma - the Latest Approach in the Ongoing Development of Strategies for Business Improvement

Six Sigma - the Latest Approach in the Ongoing Development of Strategies for Business Improvement. Use of analytical methods has grown steadily for over 80 years Statistical quality control (origins in 1920, explosive growth during WW II, 1950s) Operations research (1940s)

395 views • 15 slides

284 views • 11 slides

Machine Learning Python: Regression Modeling

Use Linear Regression to solve business problems and master the basics of Machine Learning The course "Machine Learning Basics: Building Regression Model in Python" teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. In this course students will learn the following: u2022 How to predict future outcomes basis past data by implementing Simplest Machine Learning algorithm u2022 How to do preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression u2022 Understand how to interpret the result of Linear Regression model and translate them into actionable insight u2022 Understanding of basics of statistics and concepts of Machine Learning u2022 Learn advanced variations of OLS method of Linear Regression u2022 Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python This course is suitable for anyone curious about machine learning or professionals beginning their data journey.

34 views • 3 slides