This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. You will learn how to find analyze data with a time component and censored data that needs outcome inference. You will learn a few techniques for Time Series Analysis and Survival Analysis. The hands-on section of this course focuses on using best practices and verifying assumptions derived from Statistical Learning.
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课程信息
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7 天免费试用
试用结束后，每月支付 US$39。
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第 6 门课程（共 6 门）
中级
完成时间大约为11 小时
英语（English）
字幕：英语（English）
您将获得的技能
- Dimensionality Reduction
- Unsupervised Learning
- Cluster Analysis
- Time Series
- K Means Clustering
7 天免费试用
试用结束后，每月支付 US$39。
可随时取消。
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 6 门课程（共 6 门）
中级
完成时间大约为11 小时
英语（English）
字幕：英语（English）
提供方
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
授课大纲 - 您将从这门课程中学到什么
完成时间为 2 小时
Introduction to Time Series Analysis
This module introduces the concept of forecasting and why Time Series Analysis is best suited for forecasting, compared to other regression models you might already know. You will learn the main components of a Time Series and how to use decomposition models to make accurate time series models.
完成时间为 2 小时
10 个视频 （总计 83 分钟）, 3 个阅读材料, 3 个测验
完成时间为 3 小时
Stationarity and Time Series Smoothing
This module introduces you to the concepts of stationarity and Time Series smoothing. Having a Time Series that is stationary is easy to model. You will learn how to identify and solve non-stationarity. Smoothing is relevant to you as it will help improve the accuracy of your models.
完成时间为 3 小时
13 个视频 （总计 110 分钟）, 3 个阅读材料, 3 个测验
完成时间为 3 小时
ARMA and ARIMA Models
This module introduces moving average models, which are the main pillar of Time Series analysis. You will first learn the theory behind Autoregressive Models and gain some practice coding ARMA models. Then you will extend your knowledge to use SARMA and SARIMA models as well.
完成时间为 3 小时
9 个视频 （总计 117 分钟）, 3 个阅读材料, 3 个测验
完成时间为 3 小时
Deep Learning and Survival Analysis Forecasts
This module introduces two additional tools for forecasting: Deep Learning and Survival Analysis. In addition to AI and Machine Learning applications, Deep Learning is also used for forecasting. Survival Analysis is a branch of Statistics first ideated to analyze hazard functions and the expected time for an event such as mechanical failure or death to happen. Survival Analysis is still used widely in the pharmaceutical industry and also in other business scenarios with limited data related to censoring, the lack of information on whether an event occurred or not for a certain observation.
完成时间为 3 小时
8 个视频 （总计 70 分钟）, 3 个阅读材料, 4 个测验
审阅
来自SPECIALIZED MODELS: TIME SERIES AND SURVIVAL ANALYSIS的热门评论
由 MB 提供May 6, 2021
A very well-structured course with useful techniques and detail guidelines. The Python code templates are also really useful when bringing into real-life problems.
由 GS 提供May 15, 2021
It is a good course to build foundation on the modeling of timerseries data. It will be good to add other lessons for anomaly detection on timeseries.
由 SD 提供Nov 23, 2021
This is an excellent course covering large areas of Time Series analysis and is a must for any one intending to learn the topics with some detail.
由 A 提供Nov 26, 2021
Clearly explaind. I am currently working on time series forecasting and predictions. This course helped me a lot about the details of the topics.
关于 IBM Machine Learning 专业证书
Machine Learning is one of the most in-demand skills for jobs related to modern AI applications, a field in which hiring has grown 74% annually for the last four years (LinkedIn). This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Machine Learning and leverage the main types of Machine Learning: Unsupervised Learning, Supervised Learning, Deep Learning, and Reinforcement Learning. It also complements your learning with special topics, including Time Series Analysis and Survival Analysis.
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