February 2022
Emily Webber talked about life on the Amazon SageMaker (machine learning) team. Machine learning specialists at Amazon Web Services help customers make the best use of machine learning resources on the cloud to solve business challenges, improve operations, and promote innovation. Join us for a look at the exciting tools and interesting problems data scientists get to work with. Emily Webber is a keynote speaker at Amazon Web Services, and has a YouTube video channel on SageMaker with 150,000+ views. In addition, the SageMakers Studio Lab is providing free accounts, sample Jupyter notebooks on github, and a Disaster Response hackathon! Contact Webber through her LinkedIn.
Thanks to Justyna Gutowska, Andrew Marfia, Michelle Rosman, and Sergio Servantez (from AI@NU) for their help with advertisements and logistics! Also, a shout-out to Huaxia Zhou for organizing the post-talk discussion about future directions for DSN. If you want to be involved, please leave your contact information in the form.
Emily Webber talked about life on the Amazon SageMaker (machine learning) team. Machine learning specialists at Amazon Web Services help customers make the best use of machine learning resources on the cloud to solve business challenges, improve operations, and promote innovation. Join us for a look at the exciting tools and interesting problems data scientists get to work with. Emily Webber is a keynote speaker at Amazon Web Services, and has a YouTube video channel on SageMaker with 150,000+ views. In addition, the SageMakers Studio Lab is providing free accounts, sample Jupyter notebooks on github, and a Disaster Response hackathon! Contact Webber through her LinkedIn.
Thanks to Justyna Gutowska, Andrew Marfia, Michelle Rosman, and Sergio Servantez (from AI@NU) for their help with advertisements and logistics! Also, a shout-out to Huaxia Zhou for organizing the post-talk discussion about future directions for DSN. If you want to be involved, please leave your contact information in the form.
January 2022
Qian Cao (Food and Drug Administration) gave a talk and about osteoporosis and invited students to apply for a summer fellowship.
Assessment of bone fragility is a key part of staging and management of osteoporosis. Bone mineral density (BMD) is commonly used for evaluating fracture risk and can be measured by quantitative computed tomography (CT) or dual-energy x-ray absorptiometry (DXA). However, bone fragility also depends on both mineral distribution and microstructure. Therefore, recent efforts have emphasized characterization of bone microarchitecture (or bone texture) as a basis for more reliable estimates of fragility and disease progression. I will briefly discuss my research in measurement of bone microstructure and development of texture biomarkers in CT. I will also discuss my experience as a research fellow at the Food and Drug Administration (FDA).
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
Qian Cao (Food and Drug Administration) gave a talk and about osteoporosis and invited students to apply for a summer fellowship.
Assessment of bone fragility is a key part of staging and management of osteoporosis. Bone mineral density (BMD) is commonly used for evaluating fracture risk and can be measured by quantitative computed tomography (CT) or dual-energy x-ray absorptiometry (DXA). However, bone fragility also depends on both mineral distribution and microstructure. Therefore, recent efforts have emphasized characterization of bone microarchitecture (or bone texture) as a basis for more reliable estimates of fragility and disease progression. I will briefly discuss my research in measurement of bone microstructure and development of texture biomarkers in CT. I will also discuss my experience as a research fellow at the Food and Drug Administration (FDA).
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
December 2021
Petter Holme (Tokyo Institute of Technology) gave a talk about Game Theory on Networks
We can understand many situations in society and nature as game-theoretical interactions over social networks. Sometimes there is feedback from the game payoffs to the social network formation, sometimes not. In this talk, I will review some of the key results in the field and my contributions (typically taking the network structures from empirical data). Finally, I will present some of the main challenges for the future, including how to integrate the game theory of social actors into large-scale climate modeling.
Thanks to Justyna Gutowska, Andrew Marfia, and Huaxia Zhou for their help with advertisements and logistics! A big thanks to Giancarlo Jusino Sanchez for the game theory on networks demo for the fall quarter default project.
Petter Holme (Tokyo Institute of Technology) gave a talk about Game Theory on Networks
We can understand many situations in society and nature as game-theoretical interactions over social networks. Sometimes there is feedback from the game payoffs to the social network formation, sometimes not. In this talk, I will review some of the key results in the field and my contributions (typically taking the network structures from empirical data). Finally, I will present some of the main challenges for the future, including how to integrate the game theory of social actors into large-scale climate modeling.
Thanks to Justyna Gutowska, Andrew Marfia, and Huaxia Zhou for their help with advertisements and logistics! A big thanks to Giancarlo Jusino Sanchez for the game theory on networks demo for the fall quarter default project.
October 2021
Omkar Ranadive (Alchera labs) gave a talk about AI, Image Analysis, and Wildfire Detection
Wildfires are a huge problem in the state of California. In 2021 alone, there have been 7,000+ wildfires in California, which have burned down over 2 million acres of land. An automated system that detects wildfires early, before they spread, can help save lives and minimize damage to land and structures. In this talk, we will discuss Alchera's Wildfire Alert System, which uses machine learning to perform early detection of wildfires. The system analyzes images in real-time from over 800 cameras and sends immediate alerts to users.
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
Omkar Ranadive (Alchera labs) gave a talk about AI, Image Analysis, and Wildfire Detection
Wildfires are a huge problem in the state of California. In 2021 alone, there have been 7,000+ wildfires in California, which have burned down over 2 million acres of land. An automated system that detects wildfires early, before they spread, can help save lives and minimize damage to land and structures. In this talk, we will discuss Alchera's Wildfire Alert System, which uses machine learning to perform early detection of wildfires. The system analyzes images in real-time from over 800 cameras and sends immediate alerts to users.
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
Sept 2021
84.51 retail data science by Caitlin Casar, Alexandra Saldan, Erik Schousboe. Thanks for a great talk that included getting from Northwestern to a retail data science position and the training pathways offered at 84.51!
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
84.51 retail data science by Caitlin Casar, Alexandra Saldan, Erik Schousboe. Thanks for a great talk that included getting from Northwestern to a retail data science position and the training pathways offered at 84.51!
Thanks to Justyna Gutowska and Andrew Marfia for their help with advertisements and logistics!
May 2021
Presentation of May 26th Data Science Night with Brian S. Martin from Abbvie and resources mentioned in the presentation:
Presentation of May 26th Data Science Night with Brian S. Martin from Abbvie and resources mentioned in the presentation:
| data_science_nights.pdf |
| rapide_process.pdf |
| rapide_-_canvas_assessment___rap_sheet_templates.pdf |
| space.pdf |
November 2020
Slides and links presented at November Data Science Night.
Slides and links presented at November Data Science Night.
| slidesdsnnov2020.pdf |
January 2020
Slides from Nicolay Markov - Introduction to Pandas and Matplotlib
Link: https://docs.google.com/document/u/0/d/13nIu-0YGjKmptJp0-szdBTPpnQ1X0xJl0jXBnFDLNrU
Slides from Nicolay Markov - Introduction to Pandas and Matplotlib
Link: https://docs.google.com/document/u/0/d/13nIu-0YGjKmptJp0-szdBTPpnQ1X0xJl0jXBnFDLNrU
November 2019
Slides from Daniel W. Linna Jr. - Artificial Intelligence and Law: Creating our Augmented, Automated, Audacious Future
Slides from Daniel W. Linna Jr. - Artificial Intelligence and Law: Creating our Augmented, Automated, Audacious Future
| linna-nico-data-science-ai-and-law-2019-11-21-04.pdf |
Slides from Nicolay Markov - Introduction to Python for beginners
Link: https://mxposed.github.io/dsn-intro/
| 2019-11-21-python-intro.pdf |
September 2019
Slides from Svetlana Levitan, PhD - IBM Developer Advocate and PMML Release Manager
IBM Cognitive Applications
Slides from Svetlana Levitan, PhD - IBM Developer Advocate and PMML Release Manager
IBM Cognitive Applications
| deployml_sep_25.pdf |
April 2019
Bring your data to work day
Bring your data to work day
March 2019
Tempus, Michael Lucas
Tempus, Michael Lucas
February 2019
Sears Deep Learning Center and Prof. Steven Platt from Northwestern Retail Analytics Council
Download Introductory talk (announcements)
Sears Deep Learning Center and Prof. Steven Platt from Northwestern Retail Analytics Council
Download Introductory talk (announcements)
December 2018
Andrew Hall, Psychology graduate student: Personality assessment in the age of big data and machine learning.
Andrew Hall, Psychology graduate student: Personality assessment in the age of big data and machine learning.
November 2018
Download introductory talk (announcements)
Download slides of talk (Introduction to Machine Learning)
Thanks to Nicholas Wagner and Abhijith Gopakumar for their great talk "Introduction to Machine Learning". Thanks to project leaders: Jordan Nelson, Ole Hexel, Dan Gifford, Ramya Gurunathan, Suman Bhandari, and many others working on their own or in small groups!
Download introductory talk (announcements)
Download slides of talk (Introduction to Machine Learning)
Thanks to Nicholas Wagner and Abhijith Gopakumar for their great talk "Introduction to Machine Learning". Thanks to project leaders: Jordan Nelson, Ole Hexel, Dan Gifford, Ramya Gurunathan, Suman Bhandari, and many others working on their own or in small groups!
October 2018
Download introductory slides
Thanks to project leaders: Dan Gifford, Andrew Hall, Nick Warner, Thomas Stoeger, and many other individual working on their own or in small groups!
Download introductory slides
Thanks to project leaders: Dan Gifford, Andrew Hall, Nick Warner, Thomas Stoeger, and many other individual working on their own or in small groups!
July 2018
Thank you to Christie Nothelfer for her nice talk on "Vision Science in Data Visualization" and Prof. Suzan van Der Lee for leading a session on hacking into environmental sensors.
Thank you to Christie Nothelfer for her nice talk on "Vision Science in Data Visualization" and Prof. Suzan van Der Lee for leading a session on hacking into environmental sensors.
June 2018
Download introductory slides
Thank you to our presenter, Caroline Groth, PostDoc in Preventive Medicine, for her talk on "Bayesian Measurement Error and Bayesian Informative Missingness Methods" and for the subsequent tutorial.
Download introductory slides
Thank you to our presenter, Caroline Groth, PostDoc in Preventive Medicine, for her talk on "Bayesian Measurement Error and Bayesian Informative Missingness Methods" and for the subsequent tutorial.
May 2018
Download introductory slides
Thank you to our presenter, Pantelis Loupos, a graduate student in Operations Management, for his talk on "Starting Cold: The Power of Social Networks in Predicting Non-Contractual Customer Behavior" (download slides here)
Thank you to our breakout group leaders:
Download introductory slides
Thank you to our presenter, Pantelis Loupos, a graduate student in Operations Management, for his talk on "Starting Cold: The Power of Social Networks in Predicting Non-Contractual Customer Behavior" (download slides here)
Thank you to our breakout group leaders:
|
Jason Chain and Rebecca Harmon for continuing their group on the comparison between the salaries and supplemental earnings of employees of the city of Chicago.
|
Thomas Stoeger for spearheading the start of a deep learning group
Ramya Gurunathan (and Ali Ehlen) for leading a k-means cluster analysis of FiveThirtyEight hate crime data by state |
April 2018
Download introductory slides
Thank you to our presenter, Kat Albrecht, a graduate student in the sociology department, for her talk on "Fundamental Data Science to Study Social Problems"
Thank you to our breakout group leaders!
Download introductory slides
Thank you to our presenter, Kat Albrecht, a graduate student in the sociology department, for her talk on "Fundamental Data Science to Study Social Problems"
Thank you to our breakout group leaders!
February 2018
Download introductory slides
This month was a hacking-only night. Thank you to our breakout group leaders:
Download introductory slides
This month was a hacking-only night. Thank you to our breakout group leaders:
|
Laura Derenge for giving an overview of Tableau.
Damiano Fantini and Luca Lonini for continuing their regular learning group surrounding Kaggle, which seems to move towards deep-learning. Jason Chain and Rebecca Harmon for continuing their group on the comparison between the salaries and supplemental earnings of employees of the city of Chicago. |
Kevin Chao and Ben Nelson for our first code clinic and "bring-your-code".
Ali Ehlen and Ramya Gurunathan for introducing our newest attendees to data science. Thomas Stoeger for a single-evening project on health indicators within the city of Chicago. NICO for additional administrational help. |
January 2018
Download introductory slides (with current announcements of NUIT, NICO, Ce-PIM)
Thank you to our presenter, Joe Germuska, from the Knight lab of Media Journalism, for his fantastic talk on "Data Journalism: Big and Small" (download slides)
Thank you to our breakout group leaders:
Thank you to our presenter, Joe Germuska, from the Knight lab of Media Journalism, for his fantastic talk on "Data Journalism: Big and Small" (download slides)
Thank you to our breakout group leaders:
|
Nicholas Wagner for teaching a group on building pipelines.
Damiano Fantini and Luca Lonini for continuing their regular learning group surrounding Kaggle, which seems to move towards deep-learning. Jason Chain and Rebecca Harmon for continuing their group on the comparison between the salaries and supplemental earnings of employees of the city of Chicago. Ali Ehlen and Ramya Gurunathan for introducing our newest attendees to data science. |
Tess Pottinger, from the Biomedical Informatics and Data Science Student group, and Sarah Ben Maamar, from the Postdoctoral Forum, for including the attendees of the data science night in the planning of an upcoming data science career event.
Our friends from NUIT for exchanging announcements, and our great institutional support from NICO - especially Yasmeen Khan and Justyna Gutowska for administrational help, and Andrew Marfia for announcements. |
November 2017
Download introductory slides
Thank you to our presenter, Adam Miller, LSSTC Data Science Fellow, for his overview of machine learning, "Scikit-learn Soup to Nuts: Developing a Machine-Learning Workflow"
Thank you to our breakout group leaders:
Download introductory slides
Thank you to our presenter, Adam Miller, LSSTC Data Science Fellow, for his overview of machine learning, "Scikit-learn Soup to Nuts: Developing a Machine-Learning Workflow"
Thank you to our breakout group leaders:
|
Adam Miller for his fantastic talk on "Scikit-learn Soup to Nuts: Developing a Machine-Learning Workflow"
Damiano Fantini for identifying the potential for hacking nights for Northwestern's community, and for - together with Luca Lonini (also Postdoctoral Forum)- leading and establishing a regular learning group surrounding Kaggle. Nicholas Wagner for teaching a group on REST APIs. Noah Guale for initiating a project to help children from underprivileged neighborhoods finding an internship. Rohit Pandit for creating and leading a project to forecast Oscar winners. |
Rebecca Harmon and Jason Chain for initiating and learning a group comparing the the salaries of employees of the city of Chicago to their supplemental earnings.
Beth Hakamy for assisting with the event co-ordination during the data science night. Chris Skovron and Jon Atwell for co-organizing the initial data science night, and Jon for organizing a project group to analyze the song lyrics of Bob Dylan. Our friends from Northwestern's Postdoctoral Forum and NUIT for sharing our announcements and for sharing their feedback of preceding data science events. NICO - especially Yasmeen Khan for on-day preparation, and Andrew Marfia for creating a professional flyer. |