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.  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. 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
End-to-end learning can be separated into two major parts(symilarly to the ""deep learning"").
Inference then is possyble, with the mashine acting upon previously gained experiance from the traning phase of the End-to-end learning.
End-to-end learning is
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
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.
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