Compute Backpropagation Derivatives
January 23, 2019
Consider two features x1, x2 for a single training set:
Consider two features x1, x2 for a single training set:
Tanh (Hyperbolic Tangent) Function Derivative of Tanh (Hyperbolic Tangent) Function
Sigmoid Function Derivative of Sigmoid Function
Why do we use Backpropagation? For example, consider the expression Fig. 1 Fig. 2 Fig. 3 Fig. 4 In Fig. 4, Backpropagation gives us the derivative of e with respect to every node (c, d) and input variables (a, b), but Forwardpropagation ONLY gives us the derivative of our output with respect to… read more »
How to approach Deeplearning.ai*: If you have not done any machine learning before this, don’t take this course first. The best starting point is Andrew Ng’s original ML course on coursera (https://www.coursera.org/learn/machine-learning) 2. After you complete that course, please try to complete part-1 of Jeremy Howard’s excellent deep learning course (http://course.fast.ai). Jeremy teaches deep learning Top-Down which is essential for… read more »