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:
Ce cours fait partie de la Spécialisation Advanced Statistics for Data Science
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Spécialisation Advanced Statistics for Data ScienceUniversité Johns-HopkinsÀ propos de ce cours
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Approx. 8 heures pour terminer
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Compétences que vous acquerrez
StatisticsLinear RegressionR ProgrammingLinear Algebra
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 4 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau avancé
Approx. 8 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Chinois (simplifié), Italien, Vietnamien, Coréen, Allemand, Russe, Turc, Anglais, Espagnol
Offert par
Université 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.
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
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 heures pour terminer
7 vidéos (Total 28 min), 4 lectures, 1 quiz
1 heure pour terminer
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 heure pour terminer
6 vidéos (Total 29 min), 2 lectures, 1 quiz
1 heure pour terminer
Linear regression
In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.
1 heure pour terminer
8 vidéos (Total 23 min), 2 lectures, 1 quiz
1 heure pour terminer
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 heure pour terminer
6 vidéos (Total 39 min), 1 lecture, 1 quiz
Avis
Meilleurs avis pour ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES
par JA8 sept. 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
par JR6 nov. 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.
par DL7 juin 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.
par JL16 mai 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...
À propos du Spécialisation 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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