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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-101-with-scikit-learn-and-stats-models/
课程评论：没有评论
课程名称：使用Scikit-learn和StatsModels的机器学习101 课程概述： 你是一位有志于成为数据科学家的学员，渴望取得专业成功吗？你是否准备好掌握将推动你数据科学职业发展的宝贵技能？很棒！你来对地方了。本课程将为你提供扎实的机器学习知识，帮助你实现梦想工作。没错，机器学习是成为数据科学家的基本技能之一，是你理解深度学习和现代数据分析技术的基础。 在本课程中，我们将探讨三个最基本的机器学习主题：线性回归、逻辑回归和聚类分析。你可能会感到惊讶，即使是神经网络爱好者（像我们这样的人）也不得不承认，这三种简单方法——线性回归、逻辑回归和聚类，才是数据科学的核心。因此，在本课程中，我们将把一个本可能复杂的主题变得易于理解和实际应用。 当然，要在数据科学的背景下教授这些技能，唯一的方法就是将统计理论与这些定量方法在Python中的实际应用相结合。这正是我们所追求的，理论与实践相辅相成。 我们为本课程开发了两个机器学习库——StatsModels和sklearn。我们的实践经验表明，它们有不同的应用场景，应当结合使用，而不是独立使用。 此外，参加本课程的另一个好处是我们非常注意数据科学理论常常被忽视的现象。你不能期望一个人跑得快，直到他学会走路。因此，我们将循序渐进，从简单到复杂构建机器学习模型。但别以为你会觉得理论乏味，恰恰相反！我们准备了一个课程，它将带给你实际成果，并激发你对这一主题的兴趣，因为它会向你展示，机器学习也是你能做到的（只要有合适的老师陪伴）。 我们希望你和我们一样对此课程感到兴奋，因为这门课程是打开你在数据科学世界中无数机会的大门。相信我，这是你会渴望完成的课程。同时，我们还提供30天退款保证，毫无风险。课程内容优秀，这对我们来说毫无疑问。我们100%相信你会喜欢它。还等什么呢？每天都是一个被错过的机会。点击“立即购买”按钮，让我们一起开始（机器）学习吧！
Are you an aspiring data scientist determined to achieve professional success?Are you ready and willing to master the most valuable skills that will skyrocket your data science career?Great! You've come to the right place.This course will provide you with the solid Machine Learning knowledge that will help you reach your dream job destination.That's right. Machine Learning is one of the fundamental skills you need to become a data scientist. It is the stepping stone that will help you understand deep learning and modern data analysis techniques.In this course, we will explore the three most fundamental machine learning topics: Linear regression Logistic regression Cluster analysisSurprised? Even neural networks geeks (like us) can't help, but admit that it's these 3 simple methods - linear regression, logistic regression and clustering that data science actually revolves around.So, in this course, we will make an otherwise complex subject matter easy to understand and apply in practice.Of course, there is only one way to teach these skills in the context of data science - to accompany statistics theory with practical application of these quantitative methods in Python.And that's precisely what we are after. Theory and practice go hand in hand here.We have developed this course with not one but two machine learning libraries - StatsModels and sklearn. As our practical experience showed us, they have different use cases and should be used together rather than independently.Yet another advantage of taking this course? We are very conscious that data science theory is often overlooked.You can't teach someone to run before they know how to walk. That's why we will start slowly and continue by building complex ML models.But don't assume you'll be bored by theory.On the contrary! We have prepared a course that will get you results and will foster your interest in the subject matter, as it will show you that machine learning is something you can do, too (with the right teacher by your side).Well, we hope you are as excited as we are, as this course is the door that can open countless opportunities in the data science world for you. This is a course you'll be actually eager to complete.On top of that we are happy to offer a 30-day money back guarantee. No risk for you. The content of the course is so outstanding , that this is a no-brainer for us We are 100% certain you will love it.Why wait any longer? Every day is a missed opportunity.Click the "Buy Now" button and let's start (machine) learning together!
