As a high-level library, it lets you define a predictive data model in just a few lines of code, and then use that model to fit your data.It’s versatile and integrates well with other Python libraries, such asmatplotlib for plotting,numpy for array vectorization, andpandas for dataframes...
15. Vectorization 16. More Vectorization Examples 17. Vectorizing Logistic Regression 18. Vectorizing Logistic Regression's Gradient Computation 19. Broadcasting in Python 20. Python-Numpy 21. Jupyter-iPython 22. Logistic Regression Cost Function Explanation ...
Sometimes apythonfunction requires a 2 dimension array and your input variable is a 1 dimension array. Thus, you will need to reshape your 1 dimension array into a 2 dimension array withnumpy’sreshapefunction. Let us convert our 1 dimension array into a 2 dimension array which has 2 rows ...
import numpy as np import numpy.random as ra import numpy.linalg as la if __name__ == "__main__": n = 10000 A = ra.random((n,n)) b = ra.random((n,)) c = np.dot(A,b) print(la.norm(c)) For example: amplxe-cl -collect hotspots -- python test.py Results in: amplxe...
I am trying to use tensorflow map_fn to do parallel computation. However it seems to me that the performance gain is not significant. Here are example code running Python 3.6.5, Tensorflow version 1.12.0 on Ubuntu 14.04 LTS, 28 duo cores...