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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Specialized Models: Time Series and Survival Analysis
IBM Skills NetworkОб этом курсе
Недавно просмотрено: 24 459
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Средний уровень
Прибл. 11 часов на выполнение
Английский
Субтитры: Английский
Приобретаемые навыки
- Dimensionality Reduction
- Unsupervised Learning
- Cluster Analysis
- Time Series
- K Means Clustering
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
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100% онлайн
Начните сейчас и учитесь по собственному графику.
Средний уровень
Прибл. 11 часов на выполнение
Английский
Субтитры: Английский
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IBM Skills Network
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.
Программа курса: что вы изучите
2 ч. на завершение
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.
2 ч. на завершение
10 видео ((всего 83 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
3 ч. на завершение
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.
3 ч. на завершение
13 видео ((всего 110 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
3 ч. на завершение
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.
3 ч. на завершение
9 видео ((всего 117 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
3 ч. на завершение
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.
3 ч. на завершение
8 видео ((всего 70 мин.)), 3 материалов для самостоятельного изучения, 4 тестов
Рецензии
- 5 stars73 %
- 4 stars14 %
- 3 stars7 %
- 2 stars4 %
- 1 star2 %
Лучшие отзывы о курсе SPECIALIZED MODELS: TIME SERIES AND SURVIVAL ANALYSIS
от партнера GS15 мая 2021 г.
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.
от партнера KP7 апр. 2022 г.
excellent and well explained course, especially for SARIMAX models.
от партнера GV16 дек. 2021 г.
I liked this course. It gives all the necessary information about classical machine learning algorithms as well as deep learning techniques
от партнера JM23 июля 2021 г.
Great course, very well taught and topics are useful for future applications
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