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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-using-r/
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课程名称：数据科学A-Z：用Python和R进行机器学习 课程概述： 如果你对数据科学和机器学习感兴趣，这门课程就是为你准备的！通过实际动手操作，你将学习数据科学和机器学习。数据科学家被Glassdoor评为最受欢迎的职业，美国的数据科学家平均工资超过120,000美元。数据科学是一项有前景的职业，可以帮助你解决世界上最有趣的问题！本课程面向完全的初学者以及那些希望进入数据科学领域的开发者。 课程适合以下人群： - 对机器学习感兴趣的任何人 - 至少具备高中数学知识并希望学习机器学习的学生 - 了解线性回归或逻辑回归等经典算法的中级学习者，想进一步深入机器学习领域 - 希望在数据科学领域开始职业生涯的大学生 - 希望提升机器学习技能的数据分析师 - 对现有工作不满意并希望成为数据科学家的个人 - 希望借助强大的机器学习工具为业务增加价值的人 数据科学的定义： 数据科学用于从数据中提取模式或洞见，以预测未来或理解客户行为。它是一个将统计学、数据分析及其相关方法统一的概念，旨在用数据理解和分析实际现象。通过挖掘大量的结构化和非结构化数据来识别模式，可以帮助组织降低成本、提高效率、发现新的市场机会，并增强竞争优势。 数据科学与机器学习的应用： - Netflix利用数据科学和机器学习分析观众观看模式，以了解用户兴趣，进而决定制作哪些原创系列。 - Flipkart和Amazon利用数据科学和机器学习理解客户购物行为，以提供更好的推荐。 - Gmail的垃圾邮件过滤器使用机器学习算法来处理电子邮件并判断邮件是否为垃圾邮件。 - 宝洁公司利用数据科学模型更清晰地了解未来需求，从而更优化地规划生产水平。 为何有些情况编程无效？ 对于一些自动化场景（例如无驾驶员的汽车），简单的编程就不够了，需要机器学习来处理复杂和危险的情况。 课程内容包括： - R和Python中的数据结构 - 向量、矩阵、数据框、因子、数值/分类变量、列表等 - R和Python中的编程 - 数据可视化 - 机器学习模型的实施 - 线性回归、逻辑回归、决策树、随机森林、神经网络、深度学习等 - 交叉验证、避免过拟合、降维技术 所有课程材料都是免费的，你可以在Windows、Linux或Mac上简单下载和安装R和Python。本课程关注“如何构建和理解”，不仅仅是“如何使用”。它不仅是“记忆事实”，而是通过实验“亲自看到”。课程设计旨在以更少的时间提供更多关于机器学习和数据科学的实践经验。 快来注册课程，开启你的未来旅程吧！
Interested in the field of Data Science & Machine Learning? Then this course is for you!Learn Data Science & Machine Learning by doing! Hands On Experience Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!This course is for those : 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 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.What is Data Science ?Data science is used to extract patterns or insights from data to predict future or to understand customer behavior and so on.Data science is a "concept to unify statistics, data analysis and their related methods" in order to "understand and analyze actual phenomena" with dataMining large amounts of structured and unstructured data to identify patterns can help an organization to reduce costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.Some Data Science and machine learning ApplicationsNetflix uses data science & machine learning to mine movie viewing patterns to understand what drives user interest, and uses that to make decisions on which Netflix original series to produce.Companies like Flipkart and Amazon uses data science and machine learning to understand the customer shopping behavior to do better recommendations.Gmail's spam filter uses data science (machine learning algorithm) to process incoming mail and determines if a message is junk or not..Proctor & Gamble utilizes data science (machine learning ) models to more clearly understand future demand, which help plan for production levels more optimally.Why Programming Won't Work in some Cases??Have you ever thought of the scenario where all the cars will be moving without a driver that means something like automated machines say for example automatic washing machine.But there is a difference.1. For automatic washing machine,we can write programs for the washing machine functionality.2. For automated cars without drivers in high traffic.Just imagine ,how complex and dangerous it will be when someone starts coding /programming for such functionalities.For cars to automate we would require something which is called "Machine Learning "COURSE DETAILS AS BELOW :DATA STRUCTURES ,etc. in R & PYTHON as follows:1. Vectors2. Matrices3. Data Frames4. Factors 5. Numerical/Categorical Variables6. List7. How to convert matrix into data framePROGRAMMING IN R &PYTHONDATA VISUALIZATIONIMPLEMENTATION OF MACHINE LEARNING MODELS as follows:1. Linear Regression & Logistic Regression2. Decision Tree3. Random Forest4.Neural Networks5. Deep learning 6. H2o framework7. Cross validation /How to avoid Over fitting8. Dimensionality Reduction Techniques LEARN FROM SCRATCH [HOW TO DO ML IN PYTHON] SEE IN REAL TIME HOW OPTIMIZATION WORKS TO GET A MACHINE LEARNING MODELAll the materials for this data science & machine learning course are FREE. You can download and install R & Python, with simple commands on Windows, Linux, or Mac.This course focuses on "how to build and understand", not just "how to use".It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. THE COURSE IS DESIGNED IN SUCH A WAY WHICH GIVES MORE OF PRACTICAL SENSE FOR MACHINE LEARNING & DATA SCIENCE IN VERY LESS AMOUNT OF TIMESo what are you waiting for ? Enroll in this course and start your future journey!!
