MICDE Webinar Series: Gabriel Ehrlich, Director, Research Seminar in Quantitative Economics, University of Michigan
Zoom Event MI, United StatesModeling the Economic Outlook in the Time of COVID-19.
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MICDE Webinar Series: Gabriel Ehrlich, Director, Research Seminar in Quantitative Economics, University of Michigan
Modeling the Economic Outlook in the Time of COVID-19
Mapping tools to visualize COVID19 data
Your DesktopThis session will be held online, and presenters will be in touch with more information after you register. This workshop will help you learn the approaches and tools to visualize […]
R IV: Visualization
Your DesktopThis session will be held online, and presenters will be in touch with more information after you register. Visualizing the results of research is a key aspect in facilitating scientific […]
SRTI: Software For Cross-Language Real-Time Data Communication
Your DesktopA BlueJeans link will be sent to all registered participants. Computer software simulation is used in virtually every discipline. These programs virtually represent small components of real-world events and behaviors, and […]
Introduction to Deep Neural Networks with Keras/TensorFlow
Your DesktopA BlueJeans link will be sent to all registered participants. 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 […]
Mapping tools for COVID-19 data – II
Your DesktopThis is the second workshop in this series and will build on the material and the techniques covered in the first workshop. We will use COVID-19 data available here https://github.com/nytimes/covid-19-data, combine […]
Introduction to Python’s NumPy library
Your DesktopA BlueJeans link will be sent to all registered participants. This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array […]
Efficient Data Exploration
Your DesktopTired of using `table` and `summary`? Or repeatedly using a `group_by %>% summarise` approach? Many are still using R inefficiently to summarize data, especially for presentation. However, data needs to […]