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Python 数据科学
分析数据，构建模型，并进行预测
2024/2/1•1 分钟阅读•4 个月前更新•
★4.7
•12850 次浏览•中级•80 小时5,399 次浏览298 今日读者67 次分享
全面的数据科学课程，涵盖 Python、pandas、NumPy、scikit-learn 和机器学习算法。
课程内容
Python 数据科学
Python基础
复习数据科学的Python基础。
NumPy 数组
使用 NumPy 进行数值计算。
数据处理
Pandas 数据框
使用 pandas DataFrame 操作数据。
数据清洗
清理和预处理混乱的数据集。
统计分析
描述性统计
计算并解释统计测量。
机器学习
线性回归
构建和评估线性回归模型。
分类模型
实现分类算法。
数据可视化
Matplotlib 和 Seaborn
创建引人入胜的数据可视化。
测验
1. pandas的主要目的是什么？
- 网页开发
- 数据处理与分析✓ Correct
- 机器学习
- 数据库管理
常见问题
How long does it take to complete?
The typical completion time varies based on your pace and dedication.
Is this course suitable for beginners?
This course is designed for students of all levels.
Are there any prerequisites?
No special prerequisites are required to start learning.
Can I learn at my own pace?
Yes, most courses allow self-paced learning.
What will I learn from this course?
You will gain comprehensive knowledge in Python 数据科学.
Is there a certificate upon completion?
Certificate availability depends on the course provider.
还有更多问题？访问 fastmdm.com 获取更多信息。
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