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:
Este curso faz parte do Programa de cursos integrados Advanced Statistics for Data Science
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Programa de cursos integrados Advanced Statistics for Data ScienceUniversidade Johns HopkinsInformações sobre o curso
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Aprox. 8 horas para completar
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Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
StatisticsLinear RegressionR ProgrammingLinear Algebra
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível avançado
Aprox. 8 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade Johns Hopkins
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.
Programa - O que você aprenderá com este curso
2 horas para concluir
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.
2 horas para concluir
7 vídeos (Total 28 mín.), 4 leituras, 1 teste
1 hora para concluir
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.
1 hora para concluir
6 vídeos (Total 29 mín.), 2 leituras, 1 teste
1 hora para concluir
Linear regression
In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.
1 hora para concluir
8 vídeos (Total 23 mín.), 2 leituras, 1 teste
1 hora para concluir
General least squares
We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome.
1 hora para concluir
6 vídeos (Total 39 mín.), 1 leitura, 1 teste
Avaliações
Principais avaliações do ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES
por JA8 de Set de 2020
This is an excellent course that enabled me to understand how multiple regression in linear models works behind the hood. The practical examples shown by the professor were very helpful. Thank you
por JR6 de Nov de 2017
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.
por JL16 de Mai de 2020
I really enjoyed the course. It was well explained and the quizzes at regular intervals were helpful. It would be great if there were some practice exercises though...
por DL7 de Jun de 2016
We need more advanced, theoretical courses on Coursera, like this one, in order to deeply understand the more general courses like Regression Models and Linear Models.
Sobre Programa de cursos integrados Advanced Statistics for Data Science
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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