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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-interview-questions-for-data-science/
课程评论：没有评论
Coursera 课程总结：Python 数据分析与数据科学 本课程旨在提供一种聚焦且高效的方法，通过实战练习为数据科学任务做准备。课程内容经过精心筛选，剔除了不必要的理论，直接切入最相关的实用材料。 课程内容涵盖了数据科学中常见的实际问题，这些问题代表了现实世界中数据科学岗位经常遇到的挑战。通过练习这些问题，您将培养解决类似问题的技能和直觉，为面试做好充分准备。 以下是课程的主要内容索引： * **缺失值处理** (Python): 如何识别并处理数据中的缺失值。 * **类别变量处理** (Python): 如何将类别变量纳入模型。 * **相关系数矩阵的作用** (Python): 理解相关系数矩阵在数据分析中的重要性。 * **变量间关系检查** (Python): 如何探查变量之间的关联性。 * **回归分析解读** (Python): 如何有效解读回归分析的结果。 * **对数变换提升回归模型** (Python): 如何利用对数变换优化回归模型表现。 * **多项式模型应用** (Python): 如何使用多项式模型进行建模。 * **过拟合（理论）**: 理解过拟合现象及其预防方法。 * **监督学习 vs 无监督学习（理论）**: 区分两种主要的机器学习范式。 * **参数模型 vs 非参数模型（理论）**: 探讨不同模型类型的特点。 本课程专注于核心主题和数据科学面试中最可能出现的问题，力求节省您的时间，让您能高效地掌握关键知识。
In this course, we aim to provide you with a focused and efficient approach to preparing for data science tasks through practical questions. I understand that your time is valuable, so I have carefully curated the content to cut out any unnecessary noise and provide you with the most relevant materials. Moving beyond theory, the course will dive into a wide range of practical data science questions. These questions have been carefully selected to represent the types of problems frequently encountered in real-world data science roles. By practicing these questions, you will develop the skills and intuition necessary to tackle similar problems during interviews.Throughout the course, we have filtered out any extraneous materials and focused solely on the core topics and questions that are most likely to come up in data science interviews. This approach will save you time and allow you to focus your efforts on what truly matters.Index:Missing values and how to handle them? (Python)What are categorical variables and how to include them into model (Python)What is a Correlation Matrix's role? (Python)How to check relationship between variables? (Python)How to interpret the regression analysis? (Python)How to improve the regression model results with logarithmic transformation? (Python)How to use polynomial model? (Python)What is an overfitting? How to prevent it? (Theory)Supervised vs Unsupervised Learning (Theory)Parametric and Non-parametric model (Theory)
