Machine Learning at Scale - Course Project
Main contact
Timeline
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January 19, 2019Experience start
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January 27, 2019Project Scope Meeting
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February 17, 2019Midway Check In
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March 16, 2019Final Presentation
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March 16, 2019Experience end
Timeline
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January 19, 2019Experience start
-
January 27, 2019Project Scope Meeting
Meeting between students and organization to confirm: project scope, communication styles, and important dates.
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February 17, 2019Midway Check In
Meeting between students and organization to ensure that progress is on track halfway through completion.
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March 16, 2019Final Presentation
Final course presentation. Any next steps, further interactions, or future planned joint work may be a topic of discussion.
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March 16, 2019Experience end
Experience scope
Categories
Skills
neural networks python modelling big data analytic problem solvingAre you trying to translate big data into actionable insights? In this project, students in York's Machine Learning Program will build models and recommendations that can be presented to broad audiences at your organization.
Although highly motivated, these are part-time students, and their time for this project is limited to a few hours per week. Their focus will be on building, validating, testing models, and optimizing runs, with 20% of their time spent on cleaning data.
Learners
1. Students will prepare a report on their findings and include details of models. If applicable, future collaborative work between students and your organization will be determined mutually.
2. Students will present key findings and recommendations to representative(s) from your organization.
Project timeline
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January 19, 2019Experience start
-
January 27, 2019Project Scope Meeting
-
February 17, 2019Midway Check In
-
March 16, 2019Final Presentation
-
March 16, 2019Experience end
Timeline
-
January 19, 2019Experience start
-
January 27, 2019Project Scope Meeting
Meeting between students and organization to confirm: project scope, communication styles, and important dates.
-
February 17, 2019Midway Check In
Meeting between students and organization to ensure that progress is on track halfway through completion.
-
March 16, 2019Final Presentation
Final course presentation. Any next steps, further interactions, or future planned joint work may be a topic of discussion.
-
March 16, 2019Experience end
Project examples
When they start this project, the student will have learned the basics of ML, and working with Python, Hadoop, Spark, MapReduce, TensorFlow/CNTK, Keras, and others. Students can contribute to your initiative by:
1. Kickstarting a project and completing the initial models or proof of concept models.
2. Exploring various modelling approaches and building a prototype; validating, testing, and fine-tuning models.
3. Preparing a report, and possibly working with your organization's employees on future developments in the project and/or on presentations to broader audiences in the business.
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Main contact
Timeline
-
January 19, 2019Experience start
-
January 27, 2019Project Scope Meeting
-
February 17, 2019Midway Check In
-
March 16, 2019Final Presentation
-
March 16, 2019Experience end
Timeline
-
January 19, 2019Experience start
-
January 27, 2019Project Scope Meeting
Meeting between students and organization to confirm: project scope, communication styles, and important dates.
-
February 17, 2019Midway Check In
Meeting between students and organization to ensure that progress is on track halfway through completion.
-
March 16, 2019Final Presentation
Final course presentation. Any next steps, further interactions, or future planned joint work may be a topic of discussion.
-
March 16, 2019Experience end