Python

Emily Grabowski

Senior Data Science Fellow, Senior Instructor, Senior Consultant
Linguistics

I am a Ph.D. student in Linguistics. My research interests include understanding how our speech production and speech perception systems constrain linguistic variation, especially as it applies to the larynx. I am also interested in integrating theoretical representations of language with speech. I approach this using a broad variety of tools/methodologies, including theoretical work, experiments, and modeling. Current projects include developing a computational tool to expedite the analysis of pitch and an online perception experiment on the relationship between pitch and perceived...

Eileen Cahill

Data Science Fellow
School of Information

Eileen is currently a first year Information Management and Systems student committed to studying human-centered design for the utility and usability of healthcare systems. She spent the last few years working in genomic research program analysis and management at the National Human Genome Research Institute. Prior to that, Eileen attended Georgetown University where she studied biology and studio art. During this time, she performed research on water contaminants in an analytical chemistry lab as well as research on estrogen mimicking compound effects on Zebrafish in a brain...

Nikita Samarin

Data Science Fellow
Electrical Engineering and Computer Science (EECS)

Nikita Samarin is a doctoral student in Computer Science in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley advised by Serge Egelman and David Wagner. His research focuses on computer security and privacy from an interdisciplinary perspective, combining approaches from human-computer interaction, behavioral sciences, and legal studies. Samarin is a member of the Berkeley Lab for Usable and Experimental Security (BLUES) and an affiliated graduate researcher at the Center for Long-Term Cybersecurity (CLTC) and the...

Ash Tan

Consultant
School of Information

Ash is a Masters of Information and Data Science student at the Berkeley School of Information. He currently studies data collection, analysis, and visualization, as well as research design and machine learning techniques. His interests include cognitive science, Wikipedia data, and privacy research.

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Frank Hidalgo Ruiz

Data Science Fellow
Chemistry

I am currently a 5th-year Chemical Biology Ph.D. student. My research focuses on understanding the mechanism by which mutations in a protein called Ras lead to tumorigenesis. More specifically, I aim to integrate high-throughput mutagenesis, coevolutionary analysis, and machine learning algorithms to generate a predictive model. Over the last year, I have built a Python package to process, analyze, and visualize Next Generation Sequencing datasets. I love collaborating across research fields and sharing my passion for data science.

Python Introduction to Machine Learning: Parts 1-2

October 21, 2021, 1:00pm
This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.
See event details for participation information.

Python Fundamentals: Parts 1-4

October 26, 2021, 2:30pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
See event details for participation information.

Python Visualization

October 22, 2021, 10:00am
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.
See event details for participation information.

Python Data Wrangling and Manipulation with Pandas

October 19, 2021, 10:00am
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.
See event details for participation information.

Python Fundamentals: Parts 1-4

October 26, 2021, 2:30pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.