End-to-end learning

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Case study notes[1]

Introduction[edit]

End-to-end learning is a type of ""deep learning"" process in which all of the parameters are trained jointly, rather than step by step. [2] Furthermore, just like in the case of ""deep learning"", in end-to-end learning machine uses previously gained human input, in order to execute its task accordingly.[3] This proces is specyfcly prevelant in the industry auntonomous cars(our 2018's case study), as this process with its benefites fitts perfectly with the car's Convolutional neural networks (CNNs).

How does it work or a deeper look[edit]

End-to-end learning can be separated into two major parts(symilarly to the ""deep learning"").


Training[4] is the first phase, in which the machine records all of the all of the paramiters human operator uses in what sort of situations(essesed by the Convolutional neural networks (CNNs)).[5]


Inference[6] then is possyble, with the mashine acting upon previously gained experiance from the traning phase of the End-to-end learning.

Examples[edit]

WIP Please include some example of how your concept is actually used. Your example must include WHERE it is used, and WHAT IS BENEFIT of it being used.

Autonomous Cars WIP

Pictures, diagrams[edit]

As one can see the masterfully edyted picture in paint by the true paint protogy on the right. The cyrcled parameters are assesed jointly(at the same time), while the entire thing still remains to be deep learning.


Training-624x291.png

External links[edit]

  • It would be helpful
  • to include many links
  • to other internet resources
  • to help fellow students
  • Please make sure the content is good
  • and don't link to a google search results, please

References[edit]