diff --git a/application.html b/application.html index 124c0b5..be98753 100644 --- a/application.html +++ b/application.html @@ -607,7 +607,7 @@

Application#

Hackweeks are participant-driven events that encourage collaboration and teamwork. We welcome people from a diverse range of career stages, experience levels, backgrounds and identities.

Participant selection will be made with the goal of enhancing the diversity of our communities and building lasting connections that foster open science and data sharing.

-

Our events are often over-subscribed so we ask that you ensure you can attend the majority of our sessions during October 23 to 27, 2023 before applying.

+

Our events are often over-subscribed so we ask that you ensure you can attend the majority of our sessions during August 19 to 23, 2024 before applying.

Selection Criteria#

diff --git a/index.html b/index.html index e702290..6ce2fc5 100644 --- a/index.html +++ b/index.html @@ -119,6 +119,71 @@

+ + +
+
+

+ About GeoSmart Hackweek +

+
+ We are in the early stages of organizing a third event as part of this series, and we need your help! Consider joining the hackweek organizing team. We will partner with you to design tutorials and projects, and provide a variety of professional development opportunities along the way. Click on the button below to learn more: +
+
+ + Organizing Team Information + + +
+
+ Ready to jump right in and apply? +
+
+ + Apply to the Organizing Team + + +
+
+

+ Past Events: +

+ + 2023 Hackweek + +
+
+ +
+
+

+ Information for Participants +

+
+ Right now we are only accepting applications for our Organizing Team. However, we would still like to hear from you if you are interested in attending as a participant! Applications for participants will open in early April. Click on the button below and we will be sure to email you as soon as the application form is available. +
+ + Participant Interest Form + + +
+
+
+ +
+ + +

@@ -130,3208 +195,15 @@

-
-
-

Schedule

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- All times listed below are UTC -7 (Pacific Daylight Time). - You might want to consult this - - Time Zone Map - - to figure out times in your location. - Tutorials will be located in - Alder Auditorium.

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- 8:30 - 9:30 -

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- -
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- Intro and welcome -

- - - -
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Getting to know each other setting the stage for our work together.

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Tutorial Lead(s)
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- - Anthony Arendt - -
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- - Nicoleta Cristea - -
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- - Charley Haley - -
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- -
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- 9:30 - 9:45 -

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- -
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- BREAK -

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- 9:45 - 10:45 -

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- CryoCloud and Jupyter Notebooks -

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Getting connected to our shared computational resources.

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Tutorial Lead(s)
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- - Tasha Snow - -
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- 10:45 - 11:00 -

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- -
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- BREAK -

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- 11:00 - 12:00 -

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- Introduction to machine learning -

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An overview of machine learning and the primary stages of typical Machine Learning workflows including data preparation, model selection, training, and visualization.

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Tutorial Lead(s)
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- - Valentina Staneva - -
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- 12:00 - 13:00 -

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- -
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- LUNCH -

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- 13:00 - 15:00 -

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- Intro to Projects -

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Overview of projects for this hackweek and how we will gather in small groups. Choosing our project team for the week.

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Tutorial Lead(s)
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- - Charley Haley - -
-
- - Steven Pestana - -
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- 15:00 - 16:00 -

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- Project Work -

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- 8:30 - 9:00 -

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- Approaches to Working in Teams -

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Discussion of best practices for collaborative work. Reflecting on the opportunities and challenges of small group work.

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Tutorial Lead(s)
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- - Naomi Alterman - -
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- 9:00 - 10:00 -

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- ML methods for regression problems Part 1 -

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Introducing neural networks

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Tutorial Lead(s)
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- - Ryan Johnson - -
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- 10:00 - 10:30 -

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- BREAK -

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- 10:30 - 12:00 -

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- Project Work -

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- 12:00 - 13:00 -

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- LUNCH -

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- 13:00 - 14:00 -

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- ML methods for regression problems Part 2 -

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Introducing tree-based methods

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Tutorial Lead(s)
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- - Ibrahim Olalekan Alabi - -
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- 14:00 - 16:00 -

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- Project Work -

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- 8:30 - 9:45 -

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- ML Workflow Management - GeoWEAVER -

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Guidance on managing reproducible ML workflows.

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Tutorial Lead(s)
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- - Ziheng Sun - -
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- 9:45 - 10:15 -

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- BREAK -

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- 10:15 - 12:00 -

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- Project work -

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- 12:00 - 13:00 -

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- LUNCH -

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- 13:00 - 13:30 -

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- Group photo -

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- 13:30 - 16:00 -

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- Project Work -

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- 8:30 - 9:30 -

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- ML for classification -

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Using ML methods for classification purposes.

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Tutorial Lead(s)
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Kehan Yang
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- 9:30 - 10:00 -

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- BREAK -

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- 10:00 - 12:00 -

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- Project Work -

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- 12:00 - 13:00 -

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- LUNCH -

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- 13:00 - 15:00 -

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- Project Work -

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- 15:00 - 16:00 -

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- Machine Learning Using Google Earth Engine -

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Tutorial Lead(s)
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Steve Greenberg
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- 8:30 - 9:00 -

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- Ideas for Community Building and Open Science -

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Setting a course for continued engagement with CUAHSI and the ML geoscience community of practice.

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Tutorial Lead(s)
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Tony Castronova
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- - Irene Garousi-Nejad - -
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- - Nicoleta Cristea - -
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- 9:00 - 10:00 -

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- Project wrap-up -

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- 10:00 - 10:30 -

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- BREAK / FOCUS GROUP -

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- 10:30 - 12:00 -

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- Sharing Project Outcomes Part 1 -

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An opportunity to show what we accomplished during the week.

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Tutorial Lead(s)
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- - Nicoleta Cristea - -
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- - Anthony Arendt - -
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- 12:00 - 13:00 -

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- LUNCH -

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- 13:00 - 13:30 -

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- Hackweek Survey -

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Complete a survey providing us with feedback for improving our program.

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Tutorial Lead(s)
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- - Mark Welden-Smith - -
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- 13:30 - 15:30 -

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- Sharing Project Outcomes Part 2 -

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An opportunity to show what we accomplished during the week.

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Tutorial Lead(s)
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- - Nicoleta Cristea - -
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- - Anthony Arendt - -
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- 15:30 - 16:00 -

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- Closing -

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Tutorial Lead(s)
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- - Nicoleta Cristea - -
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Meet the team

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- The people on this page have helped organize the hackweek. You'll find a few specializations listed per person if you're wondering who to reach out to during the event! -
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Nicoleta Cristea
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Research Scientist
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- Lead Hackweek Organizer badge -
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- - - Read more → - -
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Anthony Arendt
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Senior Data Science Fellow
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- Lead Hackweek Organizer badge -
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- - - Read more → - -
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Mark Welden-Smith
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Program Manager
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- Program Manager badge -
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Charley Haley
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Participant Interaction and Collaboration Architect
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- Lead Community Building badge -
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Scott Henderson
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Research Scientist
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- Lead of Technology badge - Tutorial Lead badge -
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Don Setiawan
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Research Software Engineer
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- Technology Specialist badge -
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Naomi Alterman
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Education Consultant
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Irene Garousi-Nejad
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Research Scientist
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- Hackweek Helper badge - Project Consultant badge -
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Aji John
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Postdoc
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- Tutorial Lead badge -
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Friedrich Knuth
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PhD Student
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- Hackweek Organizer badge -
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Steven Pestana
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Research Scientist
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- Hackweek Organizer badge -
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Morgan Sanger
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PhD Student
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- Hackweek Helper badge -
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Ziheng Sun
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Research Scientist
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- Tutorial Lead badge -
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Tasha Snow
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Postdoctoral Researcher
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- CryoCloud Lead badge - Tutorial Lead badge -
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Ann Nykamp
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Grants Manager
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Ibrahim Olalekan Alabi
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Graduate Student
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- Tutorial Lead badge -
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Ryan Johnson
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AI/ML Research Scientist
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- Tutorial Lead badge -
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Valentina Staneva
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Data Scientist
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- Tutorial Lead badge - Hackweek Helper badge -
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- About GeoSmart Hackweek -

-
- Hackweeks are participant-driven events that strive to create welcoming spaces for participants to learn new things, build community and gain hands-on experience with collaboration and team science.

The 2024 GeoSmart Hackweek will focus primarily on project work, with an emphasis on applications in Hydrology and Cryosphere science. Project ideas will be shared in advance. There will be space for new ideas to emerge during the Hackweek based on participant engagement. We will provide about 5 hours of data science tutorials spread over the week, including space for participant-led tutorials.

During the week, participants will have the opportunity to collaborate with their peers, share ideas, and work on projects leading to exciting results and discoveries. This event is open to all experience levels in machine learning knowledge, so whether you're a seasoned pro or just starting out, you're welcome to join. However, to benefit most from the event, prior knowledge of Python programming and data handling using common Python packages (pandas, xarray, etc.) is desired. See the event Jupyter book for more details.

Preliminary project ideas include streamflow prediction from SAR-derived snowmelt timing or snow data, predicting snow water equivalent with machine learning, glacier dh/dt from DEMs using geospatial time series analysis, derivation of snow covered areas from satellite imagery, derivation of snow depth from SAR backscatter and lidar-derived snow data, predicting river discharge from seismic waves and others! Join one of these projects or pitch your own project idea at the event! -
-
-
-
-

- -

-
-
-
    - - Brainstorming sessions - : participants can join an existing project or come up with ideas for projects that can be implemented using machine learning. -
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    - - Tutorials - : learn about common machine learning workflows, computational environments, reproducibility, and workflow management. -
-
    - - Data preparation - : explore datasets to identify and engineer relevant variables that can be used to build machine learning models. -
-
    - - Models - : work on building machine learning models using popular libraries such as TensorFlow, PyTorch, or scikit-learn. -
-
    - - Model validation and optimization - : validate models using cross-validation and other techniques to ensure that models are robust and accurate; fine-tuning hyperparameters, using feature engineering techniques, or other methods. -
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    - - Presentations - : participants can share the results from projects to receive feedback from their peers. -
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    - - Networking - : facilitated opportunities for networking and community building will be provided. -
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diff --git a/projects/list_of_projects.html b/projects/list_of_projects.html index a3a02c6..8131195 100644 --- a/projects/list_of_projects.html +++ b/projects/list_of_projects.html @@ -551,7 +551,7 @@

List of Projects

List of Projects#

-

Here is our current list of project for our October 23 to 27, 2023 GeoSmart Hackweek hackweek:

+

Here is our current list of project for our August 19 to 23, 2024 GeoSmart Hackweek hackweek:

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Project Name (with link to GitHub repo)