dlab-berkeley Goto Github PK

r-deep-learning

Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis, visualization

r-for-data-science

D-Lab R-intensive teaching materials

r-functional-programming

The joy and power of functional programming in R

r-fundamentals

D-Lab's 4 part, 8 hour introduction to R Fundamentals. Learn how to create variables and functions, manipulate data frames, make visualizations, use control flow structures, and more, using R in RStudio.

r-geospatial-fundamentals

D-Lab's 6-hour introduction to working with geospatial data in R. Learn how to import, visualize, and analyze geospatial data in R.

r-machine-learning

D-Lab's 4-hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.

r-package-development

R package development workshop

r-push-ins

D-Lab's 4.5 hour "push-in" introduction to R, providing a brief survey of foundational R concepts and operations.

r-research-design

regex-intro

regular-expressions-in-python

rstudio-project-management

Resources to help you start managing data science projects.

sas-analysis

Data Analysis with SAS

sas-intro

Introduction to SAS

search-apis

Examples of how to use google (and perhaps other) search APIs (i.e. web search from a script).

sql-for-r-users

SQL for R Users, Workshop

stata-fundamentals

D-Lab's 9 hour introduction to performing data analysis with Stata. Learn how to program, conduct data analysis, create visualization, and conduct statistical analyses in Stata.

unsupervised-learning-in-r

Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).

visualization-in-excel

web-scraping-examples

Examples of using a variety of web scraping tools and methods for various kinds of data extracted from the web