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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-professional/
课程评论：没有评论
**Become Certified Machine Learning Professional 课程总结** 本课程“成为认证机器学习专业人士”为从初学者到专业人士的机器学习工程师量身定制，旨在循序渐进地带领学员掌握机器学习的方方面面。 **核心内容概览：** * **基础知识夯实：** 课程从Python、NumPy和Matplotlib的基础知识开始，为机器学习的学习打下坚实的编程基础。同时，还将涵盖数据科学和Pandas的基础概念。 * **经典机器学习算法：** 深入学习多种核心机器学习算法，包括： * 线性回归（单变量与多变量） * 逻辑回归（单变量与多变量） * 决策树 * 随机森林 * 朴素贝叶斯 * 支持向量机（SVM） * **进阶主题：** 探索更高级的机器学习技术，如： * 集成学习（Ensemble Learning） * K折交叉验证（K-fold Method） * 无监督学习（Unsupervised Learning） * 特征工程（Feature Engineering） * 深度学习（Deep Learning） * 异常值检测（Outlier Detection） * 独热编码（One Hot Encoding） * **实践应用：** 通过实际项目，将所学概念应用于数据，提升实战能力。 **课程目标受众：** 本课程适合所有对机器学习感兴趣的人群，包括： * 具备高中数学基础，希望入门机器学习的学生。 * 已掌握线性回归、逻辑回归等基础算法，希望深入了解机器学习各领域的中间学习者。 * 对机器学习感兴趣但代码能力不强的初学者，希望轻松应用到数据集中。 * 希望开启数据科学职业生涯的大学在读生。 * 希望提升机器学习技能的数据分析师。 * 渴望转型成为数据科学家的在职人士。 * 希望通过机器学习工具为业务创造价值的各界人士。 总而言之，这是一门全面且实用的机器学习课程，旨在帮助学员从零开始，逐步成长为具备专业技能的机器学习工程师。
This course is designed for beginner to pro-level machine learning engineers. In this course, we will start from the very basics and will go to an advanced level. I have designed this course in a way that everybody can understand easily. Additionally, I have given tutorials for python,Numpy and matplotlib because these are very important for machine learning. In the end, we will do some practical projects and will apply all the concepts which we have learnt so far. We will see these conceptsLinear Regression(Single Variable and Multiple Variable)Logistic Regression(Single Variable and Multiple Variable)Decision TreeRandom ForestNaive-BayesSupport Vector MachineEnsemble LearningK-fold MethodUnsupervised LearningFeature EngineeringDeep LearningOutlier DetectionOne Hot EncodingBasics of pythonBasics of NumPyBasics of PandasBasics of Data-ScienceBasics of matplotliband much moreWho this course is for:Anyone interested in Machine Learning.Students who have at least high school knowledge in math and who want to start learning Machine Learning.Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.Any students in college who want to start a career in Data Science.Any data analysts who want to level up in Machine Learning.Any people who are not satisfied with their job and who want to become a Data Scientist.Any people who want to create added value to their business by using powerful Machine Learning tools.
