Multilevel modeling is the state-of-the-art approach for handling data with complex dependence structure in a regression analysis. This workshop will discuss fitting multilevel models in Python using the Statsmodels package. […]
What can we learn from neurochemical and cellular perturbations of in vitro neuronal network dynamics?
BRIDGING THE DIVIDE: FOSTERING INTERDISCIPLINARY COLLABORATIVE RESEARCH IN COMPUTATIONAL COGNITIVE NEUROSCIENCE
Do you have experience in working alongside community partners in data analysis or program evaluation? Do you want to connect with others who are using their skills for public good? […]
Survival analysis is used when working with data that may be censored, as often is the case in studies of human subjects with incomplete follow-up. The presence of censoring makes […]
Nonlinear relationships abound in nature, though typical statistical models ignore this in favor of simplicity, often at a cost of both predictive capabilities and better understanding of the underlying phenomenon […]
This course will cover 4 areas: Logging into the cluster How to upload your data How to run a job How to get your data from the cluster Prerequisites: Workshop […]
This course will cover 4 areas: Logging into the cluster How to upload your data How to run a job How to get your data from the cluster Prerequisites: Workshop […]
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including […]
Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This hands-on workshop will help you understand the power (and limitation) of GEE […]