- Hands-On Data Science and Python Machine Learning
- Frank Kane
- 149字
- 2021-07-15 17:14:59
Data structures
Let's move on to data structures. If you need to pause and let things sink in a little bit, or you want to play around with these a little bit more, feel free to do so. The best way to learn this stuff is to dive in and actually experiment, so I definitely encourage doing that, and that's why I'm giving you working IPython/Jupyter Notebooks, so you can actually go in, mess with the code, do different stuff with it.
For example, here we have a distribution around 25.0, but let's make it around 55.0:
import numpy as np
A = np.random.normal(55.0, 5.0, 10)
print (A)
Hey, all my numbers changed, they're closer to 55 now, how about that?

Alright, let's talk about data structures a little bit here. As we saw in our first example, you can have a list, and the syntax looks like this.
推薦閱讀
- Linux核心技術(shù)從小白到大牛
- Java Web基礎(chǔ)與實(shí)例教程(第2版·微課版)
- MATLAB圖像處理超級學(xué)習(xí)手冊
- PHP 編程從入門到實(shí)踐
- 深度強(qiáng)化學(xué)習(xí)算法與實(shí)踐:基于PyTorch的實(shí)現(xiàn)
- Interactive Applications Using Matplotlib
- Learn React with TypeScript 3
- 21天學(xué)通C++(第5版)
- MySQL程序員面試筆試寶典
- Mastering Apache Storm
- Android系統(tǒng)下Java編程詳解
- Drupal Search Engine Optimization
- 軟硬件綜合系統(tǒng)軟件需求建模及可靠性綜合試驗(yàn)、分析、評價(jià)技術(shù)
- INSTANT PLC Programming with RSLogix 5000
- Java EE輕量級解決方案:S2SH