SciPy is a free and open-source Python library used for technical computing and scientific computing. SciPy contains modules for optimizationlinear algebraintegrationinterpolationspecial functionsFFTsignal and image processingODE solvers and other tasks common in science and engineering. In this lecture, we introduce all SciPy’s functions one will most probably pass through when Jupyter Notebook on Google Chrome, which is one of my favorite. Finally, the lecture is outlined as follows:

00:00 Intro
00:21 What is SciPy ?
02:06 SciPy subpackages
05:15 Installing SciPy
08:34 Concatenate of NumPy
09:03 Concatenating by rows
09:51 Concatenating by columns
10:34 Slicing Matrices
11:01 Mesh Grids
12:17 Polynomials
13:02 Polynomial Multiplication
13:32 Integrating Polynomials
14:17 Polynomial Derivatives
15:02 Polynomial as Array
15:31 Vectorizing Functions
18:52 Special SciPy Functions
19:15 Airy Functions
22:35 Exponentially Scaled Airy Functions
24:43 Bessel Functions
25:44 Thin Drumhead Example
31:51 Logit Function
33:18 Gamma Function
35:56 Error Functions
37:04 Entropy Function
38:01 Huber Function

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