Machine Learning

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Below are the consultant we have available with Machine Learning and other expertise listed.

R Machine Learning with tidymodels: Parts 1-2

October 9, 2023, 2:00pm
Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. During this two part workshop, we will discuss basic features of supervised machine learning algorithms including k-nearest neighbor, linear regression, decision tree, random forest, boosting, and ensembling using the tidymodels framework. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

Thomas Lai

Consulting Drop-In Hours: Fri 3pm-5pm

Consulting Areas: Python, Matlab, APIs, Data Manipulation and Cleaning, Data Science, Data Visualization, Machine Learning, Python Programming, Software Tools, Git or Github, Spotfire

Quick-tip: the fastest way to speak to a consultant is to first submit a...

Suraj Nair

Data Science Fellow
School of Information

I am a PhD Student at the School of Information. My research interests lie at the intersection of development economics and machine learning, with a focus on the use of large scale digital data and new computational tools to study pressing issues in global development.

Enrique Valencia López

Data Science Fellow
Graduate School of Education

Enrique Valencia López is a PhD student in the Policy, Politics and Leadership cluster at the Graduate School of Education.His research interests relate to three broad areas: the stratification of education by gender, immigration status and ethnicity; the measurement of teacher working conditions and well-being; and education in Latin America.

Before coming to Berkeley, Enrique worked for Mexico’s National Institute for Educational Evaluation and Assessment (INEE) in both the Policy and Indicators area. During that time, he co-authored Mexico’s first report on the educational...

Cheng Ren

Senior Data Science Fellow
School of Social Welfare

Cheng Ren is a D-Lab Senior Data Science Fellow and a Ph.D. student at the School of Social Welfare. His research interests are community engagement and assessment, nonprofit development, community database, computational social welfare, and data for social goods.

Aniket Gupta

Discovery Fellow
School of Information

I am a first year masters student at UC Berkeley school of Information majoring in Information Management and Systems with a focus on Data Science and ML. I like to build optimized yet simple and scalable solutions powered by data using emerging AI technologies.

Sanjana Gajendran


I'm a second year MIMS Student with a focus on Data Science and Natural Language Processing. During the Summer 2023, I interned at Genentech as a Data Science Intern.

Python Deep Learning: Parts 1-2

June 12, 2023, 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.
See event details for participation information.

R Deep Learning: Parts 1-2

April 19, 2023, 9:00am
This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.

Python Machine Learning for Data Science Discovery

March 22, 2023, 7:00pm
Overview of Machine learning, Methods of Linear Regression, Logistic Regression (Classification), and Data Preprocessing. The workshop will consist of a live coding demo with a live question-answer session.