Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:
Этот курс входит в специализацию ''Специализация Advanced Statistics for Data Science'
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Об этом курсе
Приобретаемые навыки
- Statistics
- Linear Regression
- R Programming
- Linear Algebra
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Университет Джонса Хопкинса
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Программа курса: что вы изучите
Background
We cover some basic matrix algebra results that we will need throughout the class. This includes some basic vector derivatives. In addition, we cover some some basic uses of matrices to create summary statistics from data. This includes calculating and subtracting means from observations (centering) as well as calculating the variance.
One and two parameter regression
In this module, we cover the basics of regression through the origin and linear regression. Regression through the origin is an interesting case, as one can build up all of multivariate regression with it.
Linear regression
In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.
General least squares
We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome.
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Лучшие отзывы о курсе ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES
Great, detailed walk-through of least squares. Linear Algebra is a must for this course. To follow the last part requires knowledge of matrix (eigen?)decomposition, which derailed me somewhat.
As the name says it's an advanced course. Take the challenge though! In my opinion the content is a must if you want to perform competently in data science.
A wonderful course to study! Prof. Brian Caffo explains so well!
Excellent experience. I have learnt a lot in different aspect of linear models as well as the coding skills from this course. Thank you.
Специализация Advanced Statistics for Data Science: общие сведения
Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.

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