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所在平台: Udemy |
课程主页: https://www.udemy.com/course/supervised-machine-learning-complete-masterclass-2023/
课程评论：没有评论
课程名称：监督式机器学习完全大师班 [2023] 课程概述：欢迎参加我们的机器学习课程！本课程通过超过7小时的视频课程，逐步讲解监督式机器学习的基本概念和技术。课程内容涵盖数据预处理、模型评估与选择等主题，并提供实践练习和项目，帮助您巩固对概念的理解。 本课程适合初学者，同时也对具有一定编程和数据分析经验的人士十分有价值。您将学习Python编程基础，并掌握数据处理与可视化的常用库，如Pandas和Matplotlib。 在掌握基础后，课程将深入探讨机器学习的核心概念，包括监督学习与非监督学习、决策树、随机森林、聚类、神经网络和深度学习。您将学习如何预处理数据、训练与评估模型，并优化模型以提高性能。 除了理论知识，您还将通过使用真实数据集进行实践，使用Python实现机器学习算法。课程结束时，您将能够将机器学习技术应用于解决各种问题，并具备在这一快速发展的领域进一步学习的能力。 无论您是学生、研究人员还是希望扩展技能的专业人士，本课程将为您提供机器学习的坚实基础，帮助您获得在该领域成功所需的知识和工具。立即加入我们，开始成为机器学习专家的旅程吧！ 学习内容包括： - 机器学习 - 人工智能 - 监督式机器学习 - 回归分析 - 数据预处理与可视化 - 使用Scikit-Learn编程 - K最近邻模型 - 决策树及支持向量机 主讲教师为Allah Ditta博士，他是一位从事监督式机器学习及数据科学教学的讲师，您将获得优质的支持和反馈，帮助您提升数据科学技能！我们期待您的参与！
< Step-by-step explanation of more than 7 hours of video lessons on Supervised Machine Learning: Complete Masterclass [2023]> Welcome to the Machine Learning course!In this comprehensive course, you will learn the fundamental concepts and techniques used in Machine Learning. We will cover a range of topics from data preprocessing to model evaluation and selection, with hands-on exercises and projects to help you build and solidify your understanding of the concepts.The course is designed for beginners, but it will also be valuable for those who have some experience in programming and data analysis. You will be guided through the basics of Python programming and the most commonly used libraries for data manipulation and visualization, such as Pandas and Matplotlib.Once you have mastered the basics, we will delve into the core concepts of Machine Learning, including supervised and unsupervised learning, decision trees, random forests, clustering, neural networks, and deep learning. You will learn how to preprocess data, train and evaluate models, and optimize them for better performance.In addition to the theory, you will also have hands-on practice using real-world datasets and implementing Machine Learning algorithms with Python. By the end of the course, you will be able to apply Machine Learning techniques to solve a wide range of problems and use cases, and have the skills to further your studies in this exciting and rapidly growing field.Whether you are a student, a researcher, or a professional looking to expand your skillset, this course will provide you with a strong foundation in Machine Learning and equip you with the knowledge and tools to succeed in the field. So, join us now and start your journey toward becoming a Machine Learning expert!What you will learn:Machine LearningArtificial IntelligenceSupervised Machine LearningSupervised ML ModelWhat is Regression?Simple LRMulti-LRPolynomial RegressionModel DevelopmentData PreprocessingRegression CodingScikit ProgrammingCollection of DataSplitting of DataPoly-Scatter PlotKNN-Model for SMLDecision TreeData Visualization for SMLSupport Vector mechanics. scatter PlotsMatplotlib GlitchesColors in ScatteringPlot Vs Scatter PlotBar PlottingMultiple Bar PlotStacked and Sub PlotsHistogram PlotData SetData DistributionAllah Ditta is your lead instructor - a Ph.D. and lecturer making a living from teaching Supervised Machine Learning, and data science. You'll get premium support and feedback to help you become more confident with data science!We can't wait to see you on the course!Enroll now, and we'll help you improve your data science skills!AD ChauhdryTayyab Rashid
