principle of urban science V

machine learning | data ethics

LSDSS 2024 time series analysis

Autoencoders and RNNs

LSDSS 2024: Manifold Learning and Autoencoders

LSDSS 2024: intro to DS

ANN101

Fermi summer school 24

Fermi summer school 24

m3

needles in rubin haystacks

Drexel colloquium

Drexel Colloquium 4/2024

RAS MMA GW

KN perspective detection with the Vera C. Rubin Observatory

FEET24

KN perspective detection with the Vera C. Rubin Observatory

DSI meeting lightening talk

SOLAR NEIGHBORHOOD ULTRACOOL DWARFS

Data Science for Everyone - ethics

generative AI

Foundations of Data Science for Everyone 13

generative AI

Data Science for (Physical) scientists

PINNs and generative AI

data science for (physical) scientists 13

convolutional neural networks

Foundations of Data Science for Everyone

CNNs

Fundations of Dta Science for Everyone

neural networks

Data Science for Physical Scientists

some notes on visualizations

Foundations of Data Science for Everyone

some notes on visualizations

data sciencefor (physical) scientists 9

clustering

MAS APS 2023 astronomy + AI

data science for (physical) scientists 8

distances, knn, intro to clustering

data science for (physical) scientists VII

MCMC

Foundations of Data Science for Everyone - IX : Clustering

Nurturing the future generations of Rubin scientists with effective, culturally responsive mentoring

Surveys23/WFIS 2023

Gravi-Gamma-Nu 2023

NSF AAAC 2023

LSST surgey strategy

CSU-LCO Student Data Workshop

VIZ metals23

some notes on visualizations

METAL23

dsu23_1

StraussLuptonFest

Copy of MLTSA11 2022

transformers

machine learning for natural and physical scientists 2023 10

autoencoders

Machine learning for natural and physical scientists 2023 8

DNN 101 - deepdreams

machine learning for natural and physical scientists 2023 5

k-NN and CARTS

machine learning for natural and physical scientists 2023 4

clustering

machine learning for natural and physical scientists 2023 3

intro to time series and regression

machine learning for natural and physical scientists 2 (2023)

probability and statistics

UD 2023 Physics 838 SN Cosmology

machine learning for natural and physical scientists 1, 2023

intro to this class

Kahn symposium

UMD seminar

UMD Colloquium Rubin LSST 2/2023

FDSfA 9

NLP

CIERA jc

NorthWestern Colloquium Rubin LSST 11/2022

CIERA seminar

NorthWestern Colloquium Rubin LSST 11/2022

FDSfA 7

CART methods