PYTHON NUMPY machine learning (10/30)
This Python Numpy Training is a French tutorial specifically for machine learning:
Numpy is the most important Python package for machine learning and data science. Numpy includes the ndarray array (n dimensions), which is an extremely powerful object in machine learning and data science. Numpy offers many methods for ndarrays. In this video, we see the different constructors used to initialize ndarray arrays:
np.array()
np.zeros()
np.ones()
np.full()
np.random.randn()
The two most important attributes to remember are:
shape
size
To develop powerful programs, remember to define the value type in np.array() with dtype = np.int16, np.float64
We also see the most useful methods for manipulating the shape of our Numpy arrays:
np.vstack
np.hstack
np.concatenate
np.reshape
np.squeeze
np.ravel
There's nothing more to remember to get started with Numpy. Ignore the other attributes and methods for now! ► Video timeline:
0:00 Intro
0:40 The Numpy array, its dimensions and shape
05:20 Initialize an ndarray: np.ones, np.zeros,
09:15 np.random.randn
12:04 np.linspace, np.arange
13:24 dtype=np.float16 np.float64
15:43 Assemble arrays: vstack hstack concatenate
18:40 np.reshape np.squeeze
22:10 np.ravel()
23:08 Exercise
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► Numpy documentation for ndarray:
https://docs.scipy.org/doc/numpy/refe...
► Numpy documentation for np.random:
https://docs.scipy.org/doc/numpy-1.16...
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