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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-machine-learning-course/
课程评论：没有评论
课程名称：使用Python的机器学习 - 完整课程与项目 课程概述：欢迎参加使用Python的机器学习 - 理论与实现课程。本课程旨在通过简化机器学习算法的工作原理及其在Python中的应用，教授学生机器学习的相关知识。课程从Python基础开始，然后涵盖机器学习的关键概念，如评估指标和特征工程。最后，深入介绍各种机器学习算法。 在本课程中，您将学习以下内容： - Python基础知识 - Pandas库的使用 - 特征工程 - 模型性能评估 - 监督学习与无监督学习 - 各种机器学习算法 具体的机器学习算法包括：线性回归、逻辑回归、K近邻算法、支持向量机、决策树、随机森林及K均值聚类。 如果您对机器学习感兴趣并希望学习这些算法的理论与Python实现，欢迎报名参加课程。您可以随时在课程问答专区提问。感谢您阅读课程介绍，祝您有美好的一天。
Welcome to the Machine Learning in Python - Theory and Implementation course. This course aims to teach students the machine learning algorithms by simplfying how they work on theory and the application of the machine learning algorithms in Python. Course starts with the basics of Python and after that machine learning concepts like evaluation metrics or feature engineering topics are covered in the course. Lastly machine learning algorithms are covered. By taking this course you are going to have the knowledge of how machine learning algorithms work and you are going to be able to apply the machine learning algorithms in Python. We are going to be covering python fundamentals, pandas, feature engineering, machine learning evaluation metrics, train test split and machine learning algorithms in this course. Course outline isPython FundamentalsPandas LibraryFeature EngineeringEvaluation of Model PerformancesSupervised vs Unsupervised LearningMachine Learning AlgorithmsThe machine learning algorithms that are going to be covered in this course is going to be Linear Regression, Logistic Regression, K-Nearest Neighbors, Support Vector Machines, Decision Tree, Random Forests and K-Means Clustering. If you are interested in Machine Learning and want to learn the algorithms theories and implementations in Python you can enroll into the course. You can always ask questions from course Q & A section. Thanks for reading the course description, have a nice day.
