Protected: Policy Gradient Methods for Reinforcement Learning with Function Approximation
June 21, 2019
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Derivative of Tanh Function
January 23, 2019
Tanh (Hyperbolic Tangent) Function Derivative of Tanh (Hyperbolic Tangent) Function
Derivative of Sigmoid Function
June 29, 2019
Sigmoid Function Derivative of Sigmoid Function
Why Backpropagation
January 23, 2019
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 »
Math Term Translate
August 28, 2018
independent variables: 自变量 dependent variable: 因变量 在函数关系式中，某个量会随一个（或几个）变动的量的变动而变动，就称为因变量。如: 。此式表示为:Y随X的变化而变化。Y是因变量，X是自变量。 ordinary differential equation (ODE): If a differential equation contains only ordinary derivatives of one or more functions with respect to a single independent variable it is said to be an ordinary differential equation (ODE). 常微分方程 partial differential equation (PDE): An equation involving only partial derivatives of one or more… read more »
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August 23, 2018
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 »