We need to study the principles of machine learning, and how it is applied into the two features. Explanation and elaboration on the principles with graphs and picture illustration is required.
computer science
Description
Independent Study
This is a research paper to study how machine learning is applied in Tesla major features: autopilot and smart summon. You may refer to this video:
https://www.youtube.com/watch?v=oBklltKXtDE
FYI, here’s an article summarising the seminar:
https://medium.com/data-science-bootcamp/tesla-and-pytorch-pytorch-developer-conference-highlights-part-3ed36f2c9d5e
We need to study the principles of machine learning, and how it is applied into the two features. Explanation and elaboration on the principles with graphs and picture illustration is required. Please note that we only have basic electronic engineering knowledge, we don’t need to completely break down and explain everything. We should focus on how Tesla make their product successful, and the knowledge of machine learning they applied. This is like a case study, but it needs to demonstrate our effort in the research of machine learning.
Explanation on principles do not require citation, but it requires citation if it involves with specific information, studies or calculations.
I have listed below sections for the paper:
- Introduction
- Principle of machine learning
- Basics of Pytorch
- How Tesla’s autopilot work
- Here are some key topics I found from the video that should be useful to explain how Tesla’s autopilot works:
- neural network
- relationship between hydra net and tasks
- how the auto pilot learn
- Machine learning in Smart Summons
- Difference between smart summons and highway autopilot
- Competitions and Areas for Improvement
Please let me know if there’s any other section you think is important or valuable to the paper.
I need to submit a draft in 24 hours, and a final paper in 3 days. The final paper has to be 10 pages long.
