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01

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02

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

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Perfil de Estudiante

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Temario

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

Evaluación y proyectos

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Bourbaki Finanzas

Ciencias de Datos

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Provide the student with the correct intuition behind data science problems and some of the algorithms to solve them, including:

The geometric interpretation

Both theoretical and practical limitations

Comparison with other algorithms

Provide the student with the necessary language to translate fluently:

The problems of Catho science to the mathematical language used in machine learning.

The algorithms exposed in the literature -either in scientific articles or textbooks- to the specific problems.

Syllabus

Block one is focused on two main objectives:

Using three algorithms (perceptron, linear regressions and logistic regressions) invite the student to the methods and language of Data Science.

Make an accurate diagnosis of the student in order to offer a better planned program for the rest of the blocks.

Perceptron (Classification)

  • Statement of a binary classification problem.
  • Stages of a learning problem.
  • Geometric interpretation of linear classification
  • Algebraic formulation of linear classification

Logistic regression (Bayesian inference)

  • Binary classification using logistic regression
  • Bayes' theorem
  • Sigmoid function and interpretation
  • Likelihood Maximization
  • Approach algorithms

Profesores del curso

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