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Results for "vectores+y+matrices"
University of Colorado Boulder
Skills you'll gain: Algebra, Linear Algebra, Mathematics
Skills you'll gain: Machine Learning, Matlab, Regression
Coursera Project Network
Skills you'll gain: Data Science, Machine Learning, Python Programming
Universidad Nacional Autónoma de México
Skills you'll gain: Geometry
Skills you'll gain: Natural Language Processing
The Hong Kong University of Science and Technology
Skills you'll gain: Calculus, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Differential Equations, Algebra, Critical Thinking, Geometry, Continuous Integration
Coursera Project Network
Skills you'll gain: Data Science, Python Programming
Vanderbilt University
Skills you'll gain: Computer Programming, Other Programming Languages, Algorithms, Theoretical Computer Science, Matlab
Universidad de los Andes
Skills you'll gain: Exploratory Data Analysis, General Statistics, Probability & Statistics, Python Programming, Mathematical Theory & Analysis, Operational Analysis, Process Analysis, Statistical Programming, Computer Programming
Johns Hopkins University
Skills you'll gain: General Statistics, Probability & Statistics, Linear Algebra, Mathematics, Regression, Algebra, Correlation And Dependence
Coursera Project Network
Skills you'll gain: Data Analysis, Data Science, Python Programming
University of Minnesota
In summary, here are 10 of our most popular vectores+y+matrices courses
- Essential Linear Algebra for Data Science: University of Colorado Boulder
- Predictive Modeling and Machine Learning with MATLAB: MathWorks
- Logistic Regression with NumPy and Python: Coursera Project Network
- Trigonometría y geometría analítica: Universidad Nacional Autónoma de México
- Vector Database Projects: AI Recommendation Systems: IBM
- Vector Calculus for Engineers: The Hong Kong University of Science and Technology
- Principal Component Analysis with NumPy: Coursera Project Network
- Mastering Programming with MATLAB: Vanderbilt University
- Introducción a la ciencia de datos aplicada: Universidad de los Andes
- Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
