Intro to TensorFlow en Español from Coursera

Este curso se enfoca en aprovechar la flexibilidad y facilidad de uso de TensorFlow 2.x y Keras para compilar, entrenar e implementar modelos de aprendizaje automático. Aprenderá sobre la jerarquía de la API de TensorFlow 2.x y conocerá los componentes principales de TensorFlow mediante ejercicios prácticos. Le mostraremos cómo trabajar con conjuntos de datos y columnas de atributos. Aprenderá a diseñar y compilar una canalización de datos de entrada de TensorFlow 2.x. Adquirirá experiencia práctica en la carga de arreglos de NumPy, imágenes y datos de texto con tf.data.Dataset, así como de datos de CSV con Pandas. También adquirirá experiencia práctica en la creación de columnas de atributos numéricas, categóricas, agrupadas en depósitos y con hash.

Además, le presentaremos las API secuencial y funcional de Keras para mostrarle cómo crear modelos de aprendizaje profundo. Hablaremos sobre las funciones de activación, pérdida y optimización. Nuestros labs prácticos sobre los notebooks de Jupyter le permitirán compilar modelos de aprendizaje automático de regresión lineal básica, y de regresión logística básica y avanzada. Aprenderá a entrenar, implementar y llevar a producción modelos de aprendizaje automático a gran escala con AI Platform de Cloud.

What's inside

Syllabus

Introducción al curso

Este curso es una introducción a TensorFlow 2.x, que incorpora la facilidad de uso de Keras para compilar modelos de aprendizaje automático. En este curso, se abarcarán el diseño y la compilación de una canalización de datos de entrada de TensorFlow 2.x., la compilación de modelos de aprendizaje automático con TensorFlow 2.x y Keras, la mejora en la exactitud de estos modelos y su correspondiente escritura para una utilización escalada.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores TensorFlow 2.x and Keras, industry-standard tools for building and deploying machine learning models

Taught by Google Cloud Training, recognized for their work in machine learning and AI

Develops skills in designing and implementing TensorFlow data pipelines, building machine learning models with TensorFlow and Keras, and improving model accuracy

Provides hands-on labs and interactive materials for practical experience

Suitable for learners with prior programming experience and a basic understanding of machine learning concepts

Emphasizes deploying and scaling machine learning models using Cloud AI Platform, which may require additional costs

Reviews summary

Introducción práctica a tensorflow y keras

Según los alumnos, este curso ofrece una sólida introducción práctica a TensorFlow 2.x y Keras. Los estudiantes valoran especialmente los laboratorios y ejercicios hands-on, que ayudan a comprender y aplicar los conceptos clave. Se cubre el trabajo con datos (tf.data) y las APIs Sequential y Functional de Keras. Si bien muchos lo encuentran excelente para principiantes o para obtener una base, algunos con más experiencia previa lo consideran algo básico en ciertas secciones. La disponibilidad del curso completamente en español es destacada como un punto muy positivo.

Aborda APIs de Keras y tf.data

"Cubre bien el uso de tf.data.Dataset para cargar datos."

"Las secciones sobre las APIs Sequential y Functional de Keras son muy útiles."

"Me gustó que se enfocara en TensorFlow 2.x con Keras."

"Explica las diferencias y usos de las APIs de Keras adecuadamente."

Accesible al estar totalmente en español

"Es genial tener un curso de esta calidad disponible en español."

"Valoro mucho poder aprender estos temas técnicos en mi idioma nativo."

"La traducción y el contenido en español son muy buenos, no se siente forzado."

"Facilita enormemente el aprendizaje para hispanohablantes."

Ofrece un fundamento sólido en TF 2.x

"Es una excelente base para quienes se inician en TensorFlow y Keras."

"Las explicaciones son claras y fáciles de seguir, ideal si vienes de cero."

"El curso me dio los fundamentos que necesitaba para empezar a trabajar con modelos simples."

"Recomendado para anyone getting started with TensorFlow."

Ejercicios útiles para aplicar conceptos

"Los laboratorios son muy buenos, me ayudaron a entender mejor cómo aplicar TensorFlow."

"Aprecio mucho los ejercicios prácticos incluidos; son esenciales para fijar el conocimiento."

"La parte hands-on con los notebooks de Jupyter fue lo más valioso para mí."

"Los labs interactivos permiten poner en práctica lo aprendido de inmediato."

Puede ser básico para avanzados, rápido en temas

"Si ya tienes algo de experiencia en ML, algunas partes serán muy básicas."

"Sentí que la sección de despliegue fue un poco apresurada."

"Hubiera deseado un poco más de detalle en ciertos temas avanzados."

"Para un nivel intermedio, tal vez se queda un poco corto en algunas explicaciones."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro to TensorFlow en Español with these activities:

Keras Model Customization Tutorials

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Deepen your understanding of Keras model customization by following guided tutorials that cover advanced techniques.

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Follow along with tutorials on how to create and train custom Keras models using the sequential and functional API.
Learn how to use Keras layers, optimizers, loss functions, and metrics to fine-tune your models.
Explore techniques for regularizing and evaluating Keras models to improve their performance and generalization capabilities.

TensorFlow Classification Project

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Apply your TensorFlow skills to a practical project by building a classification model to solve a real-world problem.

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Define the problem you want to solve and gather the necessary data.
Design and implement a TensorFlow model for the classification task.
Train and evaluate your model on the dataset.
Deploy your model to a platform or application for real-world use.

TensorFlow Best Practices Blog Post

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Enhance your understanding and help others by sharing your knowledge and insights on TensorFlow best practices in a blog post.

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Identify common challenges and pitfalls in TensorFlow development.
Research and gather information on best practices and techniques.
Create a well-written and informative blog post summarizing your findings.

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Career center

Learners who complete Intro to TensorFlow en Español will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and maintains machine learning models and algorithms. TensorFlow is an open-source machine learning library that makes it easy for Machine Learning Engineers to build and train machine learning models. By taking this course, you will acquire the knowledge and skills to use TensorFlow to build and train your own machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist collects, analyzes, and interprets data to help organizations make better decisions. TensorFlow is a powerful tool that can be used to analyze and interpret data. By taking this course, you will learn how to use TensorFlow to analyze data and solve real-world problems.

See salaries and explore the career path for Data Scientist

Software Engineer

A Software Engineer designs, develops, and maintains software applications. TensorFlow is a popular machine learning library that can be used to develop and maintain machine learning applications. By taking this course, you will learn how to use TensorFlow to develop and maintain your own machine learning applications.

See salaries and explore the career path for Software Engineer

Data Analyst

A Data Analyst collects, analyzes, and interprets data to help organizations make better decisions. TensorFlow is a powerful tool that can be used to analyze and interpret data. By taking this course, you will learn how to use TensorFlow to analyze data and solve real-world problems.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

A Quantitative Analyst develops and uses mathematical and statistical models to analyze and forecast financial data. TensorFlow is a powerful tool that can be used to develop and use mathematical and statistical models. By taking this course, you will learn how to use TensorFlow to develop and use your own financial models.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

An Operations Research Analyst develops and uses mathematical and statistical models to solve complex business problems. TensorFlow is a powerful tool that can be used to develop and use mathematical and statistical models. By taking this course, you will learn how to use TensorFlow to develop and use your own models to solve complex business problems.

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Business Analyst

A Business Analyst analyzes and interprets business data to help organizations make better decisions. TensorFlow is a powerful tool that can be used to analyze and interpret business data. By taking this course, you will learn how to use TensorFlow to analyze business data and solve real-world problems.

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Product Manager

A Product Manager develops and manages products and services. TensorFlow is a powerful tool that can be used to develop and manage machine learning products and services. By taking this course, you will learn how to use TensorFlow to develop and manage your own machine learning products and services.

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Marketing Manager

A Marketing Manager develops and manages marketing campaigns and strategies. TensorFlow is a powerful tool that can be used to develop and manage machine learning marketing campaigns and strategies. By taking this course, you will learn how to use TensorFlow to develop and manage your own machine learning marketing campaigns and strategies.

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Sales Manager

A Sales Manager develops and manages sales teams and strategies. TensorFlow is a powerful tool that can be used to develop and manage machine learning sales teams and strategies. By taking this course, you will learn how to use TensorFlow to develop and manage your own machine learning sales teams and strategies.

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Customer Success Manager

A Customer Success Manager helps customers succeed with a company's products and services. TensorFlow is a powerful tool that can be used to help customers succeed with a company's machine learning products and services. By taking this course, you will learn how to use TensorFlow to help customers succeed with your company's machine learning products and services.

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Technical Writer

A Technical Writer writes and edits technical documentation. TensorFlow is a powerful tool that can be used to write and edit technical documentation. By taking this course, you will learn how to use TensorFlow to write and edit your own technical documentation.

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Teacher

A Teacher teaches students about a particular subject. TensorFlow is a powerful tool that can be used to teach students about machine learning. By taking this course, you will learn how to use TensorFlow to teach your own students about machine learning.

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Librarian

A Librarian helps people find and access information. TensorFlow is a powerful tool that can be used to help people find and access information about machine learning. By taking this course, you will learn how to use TensorFlow to help people find and access information about machine learning.

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Archivist

An Archivist preserves and manages historical records. TensorFlow is a powerful tool that can be used to preserve and manage historical records about machine learning. By taking this course, you will learn how to use TensorFlow to preserve and manage your own historical records about machine learning.

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