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Learn Linear Models, earn certificates with paid and free online courses from Harvard, MIT, University of Pennsylvania, Johns Hopkins and other top universities around the world. Read reviews to decide if a class is right for you.
Learn to use R programming to apply linear models to analyze data in life sciences.
An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. -- Part of the MITx MicroMasters program in Statistics and Data Science.
Explore the expressive power and functional capabilities of linear models in machine learning, focusing on their versatility and practical applications.
Explore fundamental concepts of linear classifiers and regressors, understanding their role in machine learning and various learning algorithms for hypothesis classification.
Aprenda a criar modelos quantitativos para análise de dados empresariais, incluindo modelos lineares, probabilÃsticos e de regressão. Domine técnicas essenciais para previsão, otimização e tomada de decisões baseadas em dados.
Comprehensive preparation for NY Regents Algebra I exam, covering key concepts through engaging lessons and assessments to ensure mastery of essential algebraic skills and exam readiness.
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.
Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.
Explore advanced linear algebra and statistics for data science, focusing on least squares regression, matrix algebra, and linear models to enhance your analytical skills and understanding.
Comprehensive R programming series for life sciences data analysis, covering statistics, linear models, high-throughput experiments, and high-dimensional data techniques to drive biomedical research and discoveries.
Master advanced statistical methods and data science techniques for rigorous analysis, informed decision-making, and evidence-based practices across industries with MIT's comprehensive program.
Explore advanced linear algebra and statistical concepts for regression modeling, enhancing your understanding of least squares, multivariate distributions, and residual analysis.
Explore in-context learning of linear models using transformers with UC Davis professor Spencer Frei in this insightful seminar.
Explore the geometry and fundamental concepts of linear classifiers, examining their role as essential tools in machine learning classification problems.
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