Informações sobre o curso
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Nível iniciante

Aprox. 22 horas para completar

Sugerido: 6 weeks of study, 2-5 hours/week...

Inglês

Legendas: Inglês, Grego, Espanhol

Habilidades que você terá

Linear RegressionVector CalculusMultivariable CalculusGradient Descent

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível iniciante

Aprox. 22 horas para completar

Sugerido: 6 weeks of study, 2-5 hours/week...

Inglês

Legendas: Inglês, Grego, Espanhol

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

What is calculus?

10 vídeos (Total 46 mín.), 4 leituras, 6 testes
10 videos
Welcome to Module 1!1min
Functions4min
Rise Over Run4min
Definition of a derivative10min
Differentiation examples & special cases7min
Product rule4min
Chain rule5min
Taming a beast5min
See you next module!39s
4 leituras
About Imperial College & the team5min
How to be successful in this course5min
Grading Policy5min
Additional Readings & Helpful References5min
6 exercícios práticos
Matching functions visually20min
Matching the graph of a function to the graph of its derivative20min
Let's differentiate some functions20min
Practicing the product rule20min
Practicing the chain rule20min
Unleashing the toolbox20min
Semana
2
3 horas para concluir

Multivariate calculus

9 vídeos (Total 41 mín.), 5 testes
9 videos
Variables, constants & context7min
Differentiate with respect to anything4min
The Jacobian5min
Jacobian applied6min
The Sandpit4min
The Hessian5min
Reality is hard4min
See you next module!23s
5 exercícios práticos
Practicing partial differentiation20min
Calculating the Jacobian20min
Bigger Jacobians!20min
Calculating Hessians20min
Assessment: Jacobians and Hessians20min
Semana
3
3 horas para concluir

Multivariate chain rule and its applications

6 vídeos (Total 19 mín.), 4 testes
6 videos
Multivariate chain rule2min
More multivariate chain rule5min
Simple neural networks5min
More simple neural networks4min
See you next module!34s
3 exercícios práticos
Multivariate chain rule exercise20min
Simple Artificial Neural Networks20min
Training Neural Networks25min
Semana
4
2 horas para concluir

Taylor series and linearisation

9 vídeos (Total 41 mín.), 5 testes
9 videos
Building approximate functions3min
Power series3min
Power series derivation9min
Power series details6min
Examples5min
Linearisation5min
Multivariate Taylor6min
See you next module!28s
5 exercícios práticos
Matching functions and approximations20min
Applying the Taylor series15min
Taylor series - Special cases10min
2D Taylor series15min
Taylor Series Assessment20min
4.7
343 avaliaçõesChevron Right

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comecei uma nova carreira após concluir estes cursos

26%

consegui um benefício significativo de carreira com este curso

Principais avaliações do Mathematics for Machine Learning: Multivariate Calculus

por DPNov 26th 2018

Great course to develop some understanding and intuition about the basic concepts used in optimization. Last 2 weeks were a bit on a lower level of quality then the rest in my opinion but still great.

por SSAug 4th 2019

Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.

Instrutores

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Samuel J. Cooper

Lecturer
Dyson School of Design Engineering
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David Dye

Professor of Metallurgy
Department of Materials
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A. Freddie Page

Strategic Teaching Fellow
Dyson School of Design Engineering

Sobre Imperial College London

Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges. Imperial students benefit from a world-leading, inclusive educational experience, rooted in the College’s world-leading research. Our online courses are designed to promote interactivity, learning and the development of core skills, through the use of cutting-edge digital technology....

Sobre Programa de cursos integrados Matemática para aprendizagem automática

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 para aprendizagem automática

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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