Learn about the use of predictive models in Python through scikit-learn. Python is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification […]
The Data Science Initiative is sponsoring a two-day workshop on February 16 and 17 highlighting recent advances on big data in brain science. The event will consist of tutorials on Feb 16 and presentations & discussions on the scientific context and data/analytic/modeling strategies on Feb 17. Date and Time February 16: 1:00 p.m. to 5:30 p.m. February 17: 8:30 […]
Big Data in Brain Science Workshop The Data Science Initiative is sponsoring a two-day workshop on February 16 and 17 highlighting recent advances on big data in brain science. The event will consist of tutorials on Feb 16 and presentations & discussions on the scientific context and data/analytic/modeling strategies on Feb 17. Date: February […]
This course builds on our Introduction to R by teaching advanced visualization and data tidying. In this course, you will cover advanced visualization including ggplot and R Shiny. In addition to visualizations, principles of tidy data and reporting will be discussed. Date: February 21, 2017 Time:9 a.m. to 5 p.m. with lunch provided Location: Donald Bren […]
Learn more about the practice of predictive modeling using Python. Description: Learn more about the practice of predictive modeling using Python. To find out about future one-day courses, please join our mailing list. This course builds upon Predictive Modeling with Python, covering best practices for building predictive models that perform well in noisy, real-world domains. […]
This course introduces Natural Language Processing to users familiar with Python. This course will introduce fundamental concepts in NLP including word and document representation, text processing, document classification, document similarity, and clustering, and dimensionality reduction. Date: March 3, 2017 Time:9 a.m. to 12:30 p.m. Location: Donald Bren Hall, Room 4011 Instructor: Garren Gaut, UC Irvine Pre-requisites: 1) A […]
This course provides an introduction to the fundamentals of the R language and its applications to data analysis. In this course, you will learn how to program in R and how to effectively use R for data analysis. The course covers an introduction to data/object types in R, reading data, creating data visualizations, accessing and […]
Learn about the use of predictive models in Python through scikit-learn. Python is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification […]
Data collected in time and/or space exhibit unique properties that require attention to draw proper conclusions from statistical analyses. In this workshop, students are introduced to statistical concepts that are particularly useful for analyzing spatial-temporal data. Using R and Python, students will learn the basic mathematics of spatial-temporal analysis via hands-on exercises, and will put […]
This course builds on our Introduction to R by teaching advanced visualization and data tidying. In this course, you will cover advanced visualization including ggplot and R Shiny. In addition to visualizations, principles of tidy data and reporting will be discussed. Date: May 12, 2017 Time:9 a.m. to 5 p.m. with lunch provided Location: Donald Bren […]