graykode/distribution-is-all-you-need

The basic distribution probability Tutorial for Deep Learning Researchers

distribution-is-all-you-need's Issues

poisson distribution

• poisson distribution is the limit of binomial distribution

• poisson distribution and gamma distribution are conjugate distributions

• poisson distribution is also useful in machine learning such as Poisson Regression

• It may be helpful if you could add it in the figure

Added ppt Attachment

Added power point attachment to make modifications and deletions free :D
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License

formatting issue in exponential.py

plt.plot(x, y, label=r'$\mu=%.2f,\ \sigma=%.2f,'
r'\ \lambda=%d$' % (u, s, lamb))
lambda should be lambda=%.2f otherwise it will only display integers.

calculate expectation and variance

The output mu, and sigma is the mean and std of the y, not the expectation(mean) and variance of the distribution, which may be confusing.
I suggest return
mu = np.sum(x * y) * step
sigma = np.sum(x * x * y) * step - mu * mu
where step is the step option in np.arange
(eg: x = np.arange(0, 1, 0.001, dtype=np.float), then step is 0.001)

For example in beta ditribution, E(x) = a/(a+b) and Var(x) = ab/((a+b)^2(a+b+1)).

I suppose mu should be E(x) and sigma should be Var(x). And I get result like this:

I also get gamma distribution result like this: