Tokyo webmining 2017-10-28
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The document discusses Python programming and data science tools like NumPy, Scikit-learn, and Cython. It provides examples of using NumPy to quickly sum a large array and speed up a prime number calculation with Cython. It also briefly mentions past Python conference talks and techniques like spectral clustering and activation functions.
![Cython
def prime(n):
p = [True] * (n + 1)
m = 2
while m < n + 1:
if p[m]:
i = m * 2
while i < n + 1:
p[i] = False
i += m
m += 1
i = n
while not p[i]:
i -= 1
return i
n
p(10000000)
Python 4.75 Cython 3.04](https://image.slidesharecdn.com/tokyowebmining-2017-10-28-171028141904/85/Tokyo-webmining-2017-10-28-15-320.jpg)
![def prime(n):
p = [True] * (n + 1)
m = 2
while m < n + 1:
if p[m]:
i = m * 2
while i < n + 1:
p[i] = False
i += m
m += 1
i = n
while not p[i]:
i -= 1
return i
def prime(int n):
cdef int i, m
p = [True] * (n + 1)
m = 2
while m < n + 1:
if p[m]:
i = m * 2
while i < n + 1:
p[i] = False
i += m
m += 1
i = n
while not p[i]:
i -= 1
return i
3.04 3.04](https://image.slidesharecdn.com/tokyowebmining-2017-10-28-171028141904/85/Tokyo-webmining-2017-10-28-16-320.jpg)
![def prime(int n):
cdef int m, i
cdef int * p = <int * >malloc((n + 1) * sizeof(int))
for i in range(n + 1):
p[i] = 1
m = 2
while m < n + 1:
if p[m]:
i = m * 2
while i < n + 1:
p[i] = 0
i += m
m += 1
i = n
while not p[i]:
i -= 1
free(p)
return i
3.04 0.17
C](https://image.slidesharecdn.com/tokyowebmining-2017-10-28-171028141904/85/Tokyo-webmining-2017-10-28-17-320.jpg)
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Tokyo webmining 2017-10-28
- 1. 2017 10 28 Web
- 4. EC ASP
- 5. • Scipy/Numpy • • • •
- 6. • • •
- 7. scikit-learn TensorFlow • • • • •
- 9. s = 0 for i in range(1, 100000001): s += i print(s) 1 1
- 10. s = sum(range(1, 100000001)) print(s)
- 11. import numpy as np a = np.arange(1, 100000001, dtype=np.int64) print(a.sum())
- 12. s = 0 for i in range(1, 100000001): s += i print(s) s = sum(range(1, 100000001)) print(s) import numpy as np a = np.arange(1, 100000001, dtype=np.int64) print(a.sum()) 30.21 12.33 0.38
- 13. Numpy • Numpy • Numpy •
- 14. Cython • Python C • • Numpy
- 15. Cython def prime(n): p = [True] * (n + 1) m = 2 while m < n + 1: if p[m]: i = m * 2 while i < n + 1: p[i] = False i += m m += 1 i = n while not p[i]: i -= 1 return i n p(10000000) Python 4.75 Cython 3.04
- 16. def prime(n): p = [True] * (n + 1) m = 2 while m < n + 1: if p[m]: i = m * 2 while i < n + 1: p[i] = False i += m m += 1 i = n while not p[i]: i -= 1 return i def prime(int n): cdef int i, m p = [True] * (n + 1) m = 2 while m < n + 1: if p[m]: i = m * 2 while i < n + 1: p[i] = False i += m m += 1 i = n while not p[i]: i -= 1 return i 3.04 3.04
- 17. def prime(int n): cdef int m, i cdef int * p = <int * >malloc((n + 1) * sizeof(int)) for i in range(n + 1): p[i] = 1 m = 2 while m < n + 1: if p[m]: i = m * 2 while i < n + 1: p[i] = 0 i += m m += 1 i = n while not p[i]: i -= 1 free(p) return i 3.04 0.17 C
- 18. Cython • • •
- 20. … • •
- 22. Premature optimization is the root of all evil. — Donald Knuth
- 24. • • • • XP •
- 25. • • •
- 26. • • •
- 27. XP • • ☓ ○ • • •
- 28. • • • • • •
- 30. • • • •
- 31. XT X
- 32. • • • • • • • •
- 33. x Softplus f(x) = log(1 + ex ) f(x) ⇡ x f(1000)
- 34. • • • • •
- 35. • Python • • • • •