Acerca de este Curso

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Resultados profesionales del estudiante

35%

comenzó una nueva carrera después de completar estos cursos

26%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Griego, Español (Spanish)

Habilidades que obtendrás

Linear RegressionVector CalculusMultivariable CalculusGradient Descent

Resultados profesionales del estudiante

35%

comenzó una nueva carrera después de completar estos cursos

26%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Griego, Español (Spanish)

ofrecido por

Logotipo de Imperial College London

Imperial College London

Programa - Qué aprenderás en este curso

Calificación del contenidoThumbs Up89%(9,476 calificaciones)Info
Semana
1

Semana 1

4 horas para completar

What is calculus?

4 horas para completar
10 videos (Total 46 minutos), 4 lecturas, 6 cuestionarios
10 videos
Welcome to Module 1!1m
Functions4m
Rise Over Run4m
Definition of a derivative10m
Differentiation examples & special cases7m
Product rule4m
Chain rule5m
Taming a beast5m
See you next module!39s
4 lecturas
About Imperial College & the team5m
How to be successful in this course5m
Grading Policy5m
Additional Readings & Helpful References5m
6 ejercicios de práctica
Matching functions visually20m
Matching the graph of a function to the graph of its derivative20m
Let's differentiate some functions20m
Practicing the product rule20m
Practicing the chain rule20m
Unleashing the toolbox20m
Semana
2

Semana 2

3 horas para completar

Multivariate calculus

3 horas para completar
9 videos (Total 41 minutos)
9 videos
Variables, constants & context7m
Differentiate with respect to anything4m
The Jacobian5m
Jacobian applied6m
The Sandpit4m
The Hessian5m
Reality is hard4m
See you next module!23s
5 ejercicios de práctica
Practicing partial differentiation20m
Calculating the Jacobian20m
Bigger Jacobians!20m
Calculating Hessians20m
Assessment: Jacobians and Hessians20m
Semana
3

Semana 3

3 horas para completar

Multivariate chain rule and its applications

3 horas para completar
6 videos (Total 19 minutos)
6 videos
Multivariate chain rule2m
More multivariate chain rule5m
Simple neural networks5m
More simple neural networks4m
See you next module!34s
3 ejercicios de práctica
Multivariate chain rule exercise20m
Simple Artificial Neural Networks20m
Training Neural Networks25m
Semana
4

Semana 4

3 horas para completar

Taylor series and linearisation

3 horas para completar
9 videos (Total 41 minutos)
9 videos
Building approximate functions3m
Power series3m
Power series derivation9m
Power series details6m
Examples5m
Linearisation5m
Multivariate Taylor6m
See you next module!28s
5 ejercicios de práctica
Matching functions and approximations20m
Applying the Taylor series15m
Taylor series - Special cases30m
2D Taylor series15m
Taylor Series Assessment20m

Revisiones

Principales revisiones sobre MATHEMATICS FOR MACHINE LEARNING: MULTIVARIATE CALCULUS

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Acerca de Programa especializado: Matemática aplicada al aprendizaje automático

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data. It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting. The third course, Dimensionality Reduction with Principal Component Analysis, uses the mathematics from the first two courses to compress high-dimensional data. This course is of intermediate difficulty and will require Python and numpy knowledge. At the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning....
Matemática aplicada al aprendizaje automático

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