لا توجد نتائج لـ "#numpypython"

NumPyは暗黙ブロードキャストがあったり、行と列の扱いが微妙なので確かにミスりやすい。 一方でMATLABは行列ネイティブな実装で、第一級オブジェクト扱い。息するようにベクトルと行列を扱える。結果として、多次元配列が別実装となるという疾患を患っており、そっちはPythonの方が良い。

初学者にPythonは難しいと思う 使える環境にあるならMATLABが無難

moccos_lab's tweet image. 初学者にPythonは難しいと思う

使える環境にあるならMATLABが無難


Illustrating Gershgorn's cirlce theorem with Python johndcook.com/blog/2021/03/1…


📅 Day 17 – Analytics Learning Log 🔹 Python (NumPy): • Learned fancy indexing & broadcasting • Solved practice questions 🔹 SQL: • Learned functions • String: TRIM, CONCAT, LEFT, RIGHT, UPPER, LOWER, REPLACE, SUBSTRING • Numeric: ROUND, ABS #DataAnalytics #Python #SQL

PranavG_23_'s tweet image. 📅 Day 17 – Analytics Learning Log

🔹 Python (NumPy):
• Learned fancy indexing & broadcasting
• Solved practice questions

🔹 SQL:
• Learned functions
• String: TRIM, CONCAT, LEFT, RIGHT, UPPER, LOWER, REPLACE, SUBSTRING
• Numeric: ROUND, ABS

#DataAnalytics #Python #SQL
PranavG_23_'s tweet image. 📅 Day 17 – Analytics Learning Log

🔹 Python (NumPy):
• Learned fancy indexing & broadcasting
• Solved practice questions

🔹 SQL:
• Learned functions
• String: TRIM, CONCAT, LEFT, RIGHT, UPPER, LOWER, REPLACE, SUBSTRING
• Numeric: ROUND, ABS

#DataAnalytics #Python #SQL
PranavG_23_'s tweet image. 📅 Day 17 – Analytics Learning Log

🔹 Python (NumPy):
• Learned fancy indexing & broadcasting
• Solved practice questions

🔹 SQL:
• Learned functions
• String: TRIM, CONCAT, LEFT, RIGHT, UPPER, LOWER, REPLACE, SUBSTRING
• Numeric: ROUND, ABS

#DataAnalytics #Python #SQL

17/♾️ When you wanna perform mathematical operations on dissimilar arrays , we use numpy broadcasting.

aiwithanu's tweet image. 17/♾️
When you wanna perform mathematical operations on dissimilar arrays , we use numpy broadcasting.
aiwithanu's tweet image. 17/♾️
When you wanna perform mathematical operations on dissimilar arrays , we use numpy broadcasting.

16/♾ When you wanna apply a filter on every pixel of your image, use np.nditer(arr)

aiwithanu's tweet image. 16/♾
When you wanna apply a filter on every pixel of your image, use np.nditer(arr)


A 😬 import numpy as np a = np.array([1, 2, 3]) print(a) for i in range(len(a)): a[i] = a[i]* 2 print(a)


高校の教科書でNumPyが教えられる時代なので、NumPyを知らない人には「高校からやり直せ」と言っていい時代になりました

tokoroten's tweet image. 高校の教科書でNumPyが教えられる時代なので、NumPyを知らない人には「高校からやり直せ」と言っていい時代になりました
tokoroten's tweet image. 高校の教科書でNumPyが教えられる時代なので、NumPyを知らない人には「高校からやり直せ」と言っていい時代になりました

In light of the foregoing discussion on social media after publication of the NumPy paper in Nature and the concerns raised about the state of diversity and inclusion on the NumPy team, we would like to issue the following statement: numpy.org/diversity_sep2… 1/7


2⃣ Get familiar with NumPy and pandas. Both NumPy and pandas are popular Python libraries, and you'll have to use them constantly during your career. These libraries aren't limited to ML applications, so you have nothing to lose by getting familiar with them. 👇


New in tf-nightly: the NumPy API. - GPU and TPU-accelerated NumPy code - Interoperable with the rest of the TF ecosystem Documentation: tensorflow.org/api_docs/pytho…

fchollet's tweet image. New in tf-nightly: the NumPy API.

- GPU and TPU-accelerated NumPy code
- Interoperable with the rest of the TF ecosystem

Documentation: tensorflow.org/api_docs/pytho…

Introducing ndindex. A new library for manipulating indices of NumPy arrays. labs.quansight.org/blog/2020/04/i… If you've ever banged your head against the wall trying to do slice arithmetic in Python, this is the library for you.


numpy.full: return an array filled with the given value Better than np.ones, np.zeros, np.empty to initialize arrays docs.scipy.org/doc/numpy/refe… (Learned it today while doing a review. Hurray for code reviews)


Almost playing doom in the jupyter notebook! Using a (new?!) canvas widget drawing #NumPy arrays with binary serialization. Thanks @maartenbreddels for the binary serialization hints and all other folks at the @ProjectJupyter widgets workshop.


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