Numpy

Applications in numpy

1. reshape numpy array .reshape()
2. generate array from a fixed range

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   np.linspace(0, 1, 100) # generate 100 values from [0, 1], each two with same gap
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   np.logspace(0, 1, 100) # generate 100 values from [10^0, 10^1], each two with same gap
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   np.random.uniform(0, 1, 100)  # randomly sampling 100 values from [0, 1)

3. generate random values array

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   np.random.randn(n, m) # array with (n x m) random values