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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/advanced-machine-learning-signal-processing
课程评论：没有评论
课程名称：高级机器学习与信号处理 课程概述： 本课程是IBM正在开发的高级数据科学专业课程的一部分，旨在提供关于监督和非监督机器学习模型的重要见解，这些模型在多个相关领域被专家广泛应用。课程中，我们将学习线性代数的基础知识，以理解机器学习模型的工作原理。随后，将介绍最流行的Python机器学习框架——Scikit-Learn和SparkML，其中SparkML占据了课程的大部分内容，因为可扩展性是解决性能瓶颈的关键。 课程将通过物联网（IoT）的实际案例来展示不同的算法应用。为了顺利通过课程，学员需要利用智能手机中的加速度传感器创建自己的振动传感器数据，因此在整个课程中将使用一个自创的真实数据集。 选择参加本课程并获得Coursera课程证书的学员，还将获得IBM数字徽章。有关IBM数字徽章的更多信息，请访问链接 ibm.biz/badging。 课程大纲： - 第一部分：搭建基础 - 第二部分：监督学习 - 第三部分：非监督学习 - 第四部分：机器学习中的数字信号处理
Part: 1
Title:Setting the stage
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Part: 2
Title:Supervised Machine Learning
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Part: 3
Title:Unsupervised Machine Learning
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Part: 4
Title:Digital Signal Processing in Machine Learning
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>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. Then we introduce the most popular Machine Learning Frameworks for python Scikit-Learn and SparkML. SparkML is making up the greatest portion of this course since scalability is key to address performance bottlenecks. We learn how to tune the models in parallel by evaluating hundreds of different parameter-combinations in parallel. We’ll continuously use a real-life example from IoT (Internet of Things), for exemplifying the different algorithms. For passing the course you are even required to create your own vibration sensor data using the accelerometer sensors in your smartphone. So you are actually working on a self-created, real dataset throughout the course. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.
