Deep Learning

Python Deep Learning: Parts 1-2

September 24, 2024, 2:00pm
The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results.

Python Deep Learning: Parts 1-2

November 18, 2024, 9:00am
The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results.

Aaron Culich

Schedule an Appointment

Consulting Areas: Python, R, SQL, AI & LLMs, APIs, Cloud & HPC Computing, Informatics, Data Wrangling, Databases & SQL, Bash or Command Line, Git or Github, Web Scraping

Kurt Soncco Sinchi

Availability: By appointment only

Consulting Areas: Python, MATLAB, Databases & SQL, Data Science, Data Visualization, Deep Learning, Geospatial Data, Maps & Spatial Analysis, Regression Analysis, Excel, Git or Github, Tableau, Natural Language Processing (NLP)

Iñigo Parra

Availability: By appointment only

Consulting Areas: Python, R, LaTeX, Data Manipulation and Cleaning, Data Science, Data Visualization, Deep Learning, Digital Humanities, Machine Learning, Natural Language Processing, Social Network Analysis, Regression Analysis, Means Tests, Bash or Command Line, Excel, Gephi, Git or Github, Qualtrics, RStudio, Overleaf

Kurt Soncco Sinchi

Consultant
Civil Engineering

First generation student and looking to improve and apply Data Science core concepts into social impactful projects, as well as trying to leverage the information from previous cases for better insights of society. Focused on infrastructure and its impact under natural disasters.

Nikita Samarin

Instructor
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...

Sohail Khan

Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Jaewon Saw

Data Science Fellow 2024-2025
Civil and Enviromental Engineering

I am a PhD candidate in Systems Engineering. My current research focuses on distributed acoustic sensing (DAS), a cutting-edge technology with diverse applications. I have used DAS to detect whale vocalizations in Monterey Bay, California, and to monitor roadways, water pipelines, and energy infrastructure.

I enjoy identifying and mitigating challenges that arise when applying new technologies by developing data tools, pipelines, and frameworks for real-world deployments. My work is driven by a keen interest in exploring and refining innovative...

Bruno Smaniotto

Data Science Fellow 2024-2025
Economics

I'm originally from Brazil, but I have been living in Berkeley for the last 5 years working towards my PhD in Economics. My main areas of interest are Behavioral and Macroeconomics, mostly their intersection, but I'm excited about learning and working on empirical applications on different fields.