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所在平台: Udemy |
课程主页: https://www.udemy.com/course/30-days-of-python-code-numpy-challenge/
课程评论：没有评论
**课程名称：** 30天Python代码：NumPy挑战 (30 Days of Python Code: NumPy Challenge) **课程概述：** 本课程是一项独特、实践导向的计划，旨在通过专注于 Python 最强大的库之一——NumPy，来提升您的 Python 编程技能。本课程非常适合那些已经掌握 Python 基础知识，并希望加深对 Python 生态系统中数值计算理解的学习者。 在 30 天的时间里，您将完成一系列编码练习，以熟悉 NumPy 库的强大功能和灵活性。课程涵盖 NumPy 的核心特性，如数组、数组索引、数据类型、数组数学、广播等。每天都会带来新的挑战，促使您应用和巩固所学知识，确保您对 NumPy 的理解全面而深入。 本课程互动性极强，让您通过实践学习，这是公认的最有效的编程学习方式之一。这种方法培养了解决实际问题和创造力，因为您需要为现实世界的编程问题找到解决方案。 此外，课程为每个编码练习提供了详细的解决方案和解释，让您可以将自己的解决方案与最佳实践进行比较。通过这种方式，您不仅能学习到正确的方法，还能深入了解其背后的逻辑，从而提高您的编码和调试技能。 本课程非常适合任何希望使用 Python 进行数据分析、数据科学或机器学习，并希望利用 NumPy 的强大功能高效处理数值数据的学习者。 **NumPy - 释放数值 Python 的强大力量！** NumPy，Numerical Python 的简称，是 Python 中科学计算的基础库。它提供了对数组、矩阵的支持，以及一系列用于操作这些数据结构的数学函数。本课程结构清晰，每个部分都针对 NumPy 库的特定特性，包括数组创建、索引、切片、操作，以及数学和统计函数。 **您将在基础练习中找到的主题包括：** * 数组创建 * 数组形状、重塑数组 * 维度 * 大小 * 索引 * 切片 * 数组操作 * 数学、统计与计算 * 日期 * 随机数 * 比较数组 * 广播 * 数组的保存、加载与导出 * 数组的追加、连接与堆叠 * 数组的排序、搜索与计数 * 过滤、布尔掩码 * 图像作为数组 * 处理缺失值 * 迭代数组 * 线性代数 * 矩阵乘法 * 多项式 * 求解方程组 * 包含字符的数组 * 函数式编程与通用函数 * 哑变量编码 * 以及其他更多内容
This course is a unique, hands-on program designed to elevate your Python programming skills by honing in on one of Python's most powerful libraries: NumPy. This course is ideal for those already comfortable with Python basics and are looking to deepen their knowledge of numerical computing within the Python ecosystem.Over the course of 30 days, you'll undertake a range of coding exercises designed to familiarize you with the power and flexibility of the NumPy library. The course covers NumPy's core features such as arrays, array indexing, datatypes, array math, broadcasting, and more. Each day presents a new challenge, pushing you to apply and reinforce what you've learned, ensuring that your understanding of NumPy is comprehensive and well-rounded.The course is highly interactive, allowing you to learn by doing, which is widely recognized as one of the most effective ways to learn programming. This approach fosters practical problem-solving skills and creativity, as you are tasked with finding solutions to real-world programming problems.In addition, the course provides detailed solutions and explanations for each coding exercise, enabling you to compare your solutions with best practices. This way, you not only learn about the correct approach, but also gain insight into the reasoning behind it, improving your coding and debugging skills.This course is perfect for anyone aiming to use Python for data analysis, data science, or machine learning, and wants to leverage the power of NumPy to work with numerical data efficiently.NumPy - Unleash the Power of Numerical Python!NumPy, short for Numerical Python, is a fundamental library for scientific computing in Python. It provides support for arrays, matrices, and a host of mathematical functions to operate on these data structures. This course is structured into various sections, each targeting a specific feature of the NumPy library, including array creation, indexing, slicing, and manipulation, along with mathematical and statistical functions.Topics you will find in the basic exercises:arrays creationshapes, reshaping arraysdimensionssizeindexingslicingarrays manipulationmath, statistic & calculationsdatesrandomcomparing arraysbroadcastingsaving, loading & exportingappending, concatenating & stacking arrayssorting, searching & countingfilteringboolean maskimage as an arraydealing with missing valuesiterating over arrayslinear algebramatrix multiplicationpolynomialssolving systems of equationsarrays with charactersfunctional programming & universal functionsdummy encodingand other
