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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-numpy/
课程评论：没有评论
课程名称：Python-NumPy 课程概述： 本课程旨在教授学员如何使用NumPy库进行科学计算，掌握NumPy在数据科学、机器学习、数据可视化和数据评估等领域的实际应用。NumPy以其高层级的语法，为快速数据处理提供了强大的支持。 课程内容将涵盖： * NumPy包的各种方法和函数，用于科学计算。 * 通过大量的练习，深入理解NumPy的使用。 * 处理和解决在NumPy使用过程中可能遇到的常见错误。 * NumPy数组的切片 (slicing) 和重塑 (reshaping) 操作。 * 将Python列表转换为NumPy数组以实现更快的处理速度。 课程前提： * 已安装Python 3 和 Anaconda。 * 熟悉使用Jupyter Notebook。 * 具备Python基础知识。 课程资源： * 提供免费下载的课程活动和练习文件。 * Jupyter Notebook练习文件包含详细的注释，帮助学员理解每一行代码的作用，方便自主练习。 授课环境： * 使用Python 3 版本。 * 使用Jupyter Notebook作为集成开发环境 (IDE)。 注意：本课程不包含Python和Anaconda的安装、下载及环境配置教程。
Learn numerical python to gain practical knowledge in how the NumPy package is used in scientific computing. NumPy is used by Data Scientists, used in the fields of machine learning, used in data visualization, used in data evaluation, and the likes with its high-level syntax. In this course, we would learn lots of different methods used in scientific computing, exploring the Numpy package with lots of exercises including handling or fixing some of the errors we might encounter, slicing, reshaping, converting a list to a NumPy array for fast processing. The course assumes you already have python3, Anaconda already installed and you're comfortable using Jupyter notebook. Also, some background understanding of python basics is okay. You'll have free -downloadable access to the course activities/ exercise from the first section of the course module. The jupyter notebook exercise file has been well commented on so you understand what we are trying to achieve with each line of code. This should help you practice on your own while watching the video. Also, more sessions will be added as they are being edited. *Python 3* is the version of python used in the lectures and Jupyter notebook is the IDE used in programming for the course. It should be noted that python and anaconda installations and downloads and setting up anaconda and python is not taught in this course.
