Welcome to Predictive Modeling, Model Fitting, and Regression Analysis. In this course, we will explore different approaches in predictive modeling, and discuss how a model can be either supervised or unsupervised. We will review how a model can be fitted, trained and scored to apply to both historical and future data in an effort to address business objectives. Finally, this course includes a hands-on activity to develop a linear regression model.
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- 5 stars65%
- 4 stars17.50%
- 3 stars7.50%
- 2 stars5%
- 1 star5%
來自PREDICTIVE MODELING, MODEL FITTING, AND REGRESSION ANALYSIS的熱門評論
course content is very concise and easy to understand
good course to understand the fundamentals of predictive analysis
Thank you Very Much I learn a lot of Thing with all kinds of Predative Modeling that I can use.
關於 Data Science Fundamentals 專項課程
This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques. The course also provides an overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations.