CHI@Edge | Education
  • CHI@Edge Education
    • Module I - Autonomous Vehicles
      • FOR EDUCATORS
      • Self-Learners
      • Pathways
        • TA Guide
        • Regular Pathway
          • Background Information
            • Software for the Project
            • Edge Devices
            • Machine Learning
            • Chi@Edge
          • Buying or Building Your Own Car
          • Adding Pi and Leasing Chameleon Node
            • Reserving your Pi on CHI@Edge
          • Car Assembly
          • Car Calibration
          • Collecting Data
          • Cleaning Data
          • Configuring Chameleon Node for Training
          • Syncing Data from Pi to Training Node
          • Training the Model
          • Syncing Model to Car
          • Running the Model
          • (Optional) Using Chameleon Object Store
          • (Optional) Simulator Setup
          • (Optional) Assignment: Extending CHI@Edge Autonomous Cars
            • Possible extensions
            • Evaluation of Different Model Types
        • Classroom Pathway
          • (Optional) Background Information
            • Software for the Project
            • Edge Devices
            • Machine Learning
            • Chi@Edge
          • (TA) Buying or Building Your Own Car
          • (TA) Adding Pi and Leasing Chameleon Node
            • Reserving your Pi on CHI@Edge
          • (TA) Car Assembly
          • (TA) Configuring Chameleon Node for Training
          • (TA) Adding Access from Pi to Training Node
          • Car Calibration
          • Collecting Data
            • Moving Data from Pi to Chameleon Node
          • Cleaning Data
          • Training the Model
          • Syncing Model to Car
          • Running the Model
          • (Optional) Assignment: Extending CHI@Edge Autonomous Cars
            • Possible extensions
        • Digital Pathway
          • Background Information
            • Software for the Project
            • Machine Learning
          • Simulator Setup
          • Collecting Data
          • Cleaning Data
          • Reserve a Bare-Metal Node
          • Configuring Chameleon Node for Training
          • Syncing Data from Local Computer to Training Node (Digital Version)
          • Training the Model
          • Syncing Model to Local Computer
          • Running the Model in Simulator
          • Possible extensions
      • FAQ
      • References
      • Resources
  • README: Pathway Structure
  • Contributing Community Modules
  • How to Provide Feedback
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Last updated 1 year ago

General Information

Machine learning is the creation of systems capable of learning and improving from "experience" and a subset of artificial intelligence. This means that instead of having to be coding a system to be able to perform a certain task in a certain way, the system learns from examples in a way similar to humans (hence artificial intelligence).

These examples can be images, words, audio, video, or a whole range of other possibilities. To read more, here is a an article on the subject published by

End-to-End Deep Learning

In this project, CHI@Edge , end-to-end deep learning is utilized. While E2E (end-to-end) deep learning is a complex topic, it can essentially be boiled down to not decomposing. This refers to how machine learning problems are usually decomposed into sub-problems.

However, E2E deep learning allows for a simplification of the learning process by having input passed to a neural network and receive an output, with relevant details abstracted by the network. For more technical details and discussion about this topic, a question called was posted on the AI Stack Exchange.

MIT.
Autonomous Cars with Donkeycar
What does end-to-end training mean
  • General Information
  • End-to-End Deep Learning
PreviousEdge DevicesNextChi@Edge
  1. CHI@Edge Education
  2. Module I - Autonomous Vehicles
  3. Pathways
  4. Regular Pathway
  5. Background Information

Machine Learning

An Overview of Machine Learning and Additional Resources for Exploration