Modeling March Madness with Python, Part 4/4
Apr
10
6:15 pm18:15

Modeling March Madness with Python, Part 4/4

This will be the third workshop in the series about using Machine Learning to model March Madness! Come out to learn about how to choose a model for your data!

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Need an impressive project for your resume? Want to destroy your friends in a bracket pool? MSU Data Science is Modeling March Madness in Python, and you're invited!

 

Learn how to scrape web pages to build your dataset and model the tournament in 4 parts!

 

Part 1: Web Scraping

Part 2: Data Mining

Part 3: Choosing a Model

Part 4: Model Evaluation

Hadley Wickham - Rstudio & Rice University
Apr
5
6:00 pm18:00

Hadley Wickham - Rstudio & Rice University

  • MSU College of Natural Science Room 326

Hadley Wickham is the Chief Scientist at Rstudio and an adjunct professor at Rice University. He has written multiple books about using R for data science and developed some of the most popular R packages for data science. Hadley is one of the most influential data scientists today and has revolutionized the way people use R and do data science.

Information regarding parking can be found here.

Modeling March Madness with Python, Part 3/4
Mar
13
6:15 pm18:15

Modeling March Madness with Python, Part 3/4

This will be the third workshop in the series about using Machine Learning to model March Madness! Come out to learn about how to choose a model for your data!

--------------------------------------------------------------------

Need an impressive project for your resume? Want to destroy your friends in a bracket pool? MSU Data Science is Modeling March Madness in Python, and you're invited!

 

Learn how to scrape web pages to build your dataset and model the tournament in 4 parts!

 

Part 1: Web Scraping

Part 2: Data Mining

Part 3: Choosing a Model

Part 4: Model Evaluation

Modeling March Madness with Python, series 2/4
Feb
28
6:30 pm18:30

Modeling March Madness with Python, series 2/4

  • South Kedzie Hall (S105)

This will be the second workshop in the series about using Machine Learning to model March Madness! Come out to learn about the coolest part of the process, Data Mining!
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Need an impressive project for your resume? Want to destroy your friends in a bracket pool? MSU Data Science is Modeling March Madness in Python, and you're invited!

Learn how to scrape web pages to build your dataset and model the tournament in 4 parts!

Part 1: Web Scraping
Part 2: Data Mining
Part 3: Choosing a Model
Part 4: Model Evaluation

 

Click here to RSVP on Facebook!

Kevin Novak - Uber
Feb
27
6:00 pm18:00

Kevin Novak - Uber

  • South Kedzie Hall S105

Kevin Novak was the Head of Data Science at Uber until January, and now helps lead data science at one of Uber's most recent acquisitions, the autonomous vehicle company Otto. Kevin has years of experience leading world class data teams and currently lives in the San Francisco Bay Area. 

He graduated from Michigan State University in 2010 with a M.S. in Physics, making him our 5th speaker alum

Click here to RSVP on Facebook!

Tracy Hewitt - Ford
Feb
15
6:00 pm18:00

Tracy Hewitt - Ford

  • Broad College Complex (BCC) N105

Please RSVP on Facebook by clicking here

Tracy Hewitt leads the Emerging Analytics Strategy and Acceleration practice for Global Data Insights and Analytics (GDI&A) at Ford Motor Company. She joined Ford in 2015 after serving as the Analytics Officer for Global Connected Customer Experience (GCCX) at General Motors.

Previously, she led a university-based consulting group that built predictive models for hospitals, Harley-Davidson, Whirlpool, Dow Chemical and more. Her degrees are in (BA, MS) in applied economics from Michigan State University, making her the 4th Spartan Alumni to speak in our series!

 

Modeling March Madness with Python Part 1/4: Web Scraping
Feb
6
6:00 pm18:00

Modeling March Madness with Python Part 1/4: Web Scraping

  • South Kedzie Hall, Room S107

Need an impressive project for your resume? Wanna destroy your friend's bracket pool? MSU Data Science is Modeling March Madness in Python, and you're invited! 

Learn how to scrape web pages to build your dataset and model the tournament in 4 parts!

Part 1: Web Scraping
Part 2: Data Mining and Feature Engineering
Part 3: Choosing a Model
Part 4: Model Evaluation

The Journey Into Data Science - Sean Law of TD Ameritrade
Jan
23
6:00 pm18:00

The Journey Into Data Science - Sean Law of TD Ameritrade

This will be a talk about how to land a data science job! Mindset and approach, writing resumes, interviewing, negotiating salaries, working in a professional setting, networking, social presence, portfolio, and more. It's an excellent opportunity get some clarity about the data science job market, a very murky topic indeed.

119 Eppley Center, pizza and pop provided! Doors open at 6. 

Find Sean on Twitter at @seanmylaw.

Nov
30
6:30 pm18:30

Brian Ball, Data Scientist at Quicken Loans

  • Eppley Center, Room 115

Please RSVP on Facebook by clicking here.

Brian Ball is the sole data scientist at Quicken Loans, and holds a PhD in Physics from the University of Michigan. His focus was in mathematical modeling of interactions between particles - something that lends itself to both network and decision sciences. After working as a Decision Scientist at Conversant, the 2nd biggest digital marketing firm after Google, he is now at Quicken Loans working on optimizing and innovating on the mortgage process.

Nov
9
6:00 pm18:00

Josh Long, Senior GIS Analyst at DataDrivenDetroit

  • Business College Complex, Room N105

Josh Long is our second MSU alum in the speaker series. Josh joined Data Driven Detroit after working as a planner in both the public and private sector. At D3 he works as a Senior GIS Analyst and Project lead. Recent projects include the implementation of the D3 ArcGIS Open Data portal, an analysis of Detroit student commuting patterns, and providing technical assistance to the Downtown Detroit Partnership for the creation of the downtown Detroit Business Improvement Zone.

Oct
20
6:30 pm18:30

Randy Olson, Sr. Data Scientist at UPenn Institute for Biomedical Informatics

  • Eppley Center, Room 116

Randy visits us from the University of Pennsylvania Institute for Biomedical Informatics. His day-to-day involves developing state-of-the-art machine learning algorithms to solve biomedical problems. Randy is probably best known for his algorithmic creation of The Optimal U.S. National Parks Centennial Road Trip, which garnered international attention and media recognition. 

Randy is also our first speaker who is an MSU Alum! He will speak about his journey into data science through the lens of a Spartan!

Oct
6
6:30 pm18:30

Gary King, Ph. D., Director Quantitative Social Sciences at Harvard

  • LOCATION: 326 NATURAL SCIENCE BUILDING

Professor King is the most esteemed academic in our speaker series. At Harvard, he develops and applies empirical methods in many areas of social science research, focusing on innovations that span the range from statistical theory to practical application.

Please RSVP on Facebook so we know how much pizza we need to get! 

Sep
27
6:30 pm18:30

Sebastian Raschka, 'Becoming a Data Scientist'

  • Wells Hall, Room B119

Sebastian authored Python Machine Learning, which is hailed as many as the seminal ML book today.

Since the release, he has been jet-setting to data science conferences around the country to give talks about Machine Learning, and more specifically, the scikit-learn package in Python.

Sebastian is Ph. D. candidate at MSU who is developing novel algorithms in the field of Computational Biology, and in collaborations with experimentalists, he's applying data science for drug discovery. We are so excited to have our first speaker ever be a Spartan!