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Nestor Nicolas Campos Rojas

En este proyecto de 1 hora, aprenderás a usar Tensorflow para desarrollar tu primera red neuronal, usango Google Colaboratory para ello.

Además, aprenderás a usar TensorflowJS para consumir el modelo desde la web, por parte de tus usuarios.

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What's inside

Syllabus

Clasificación de imágenes con Tensorflow
Al final de este proyecto, tú entenderás Tensorflow y su forma de utilización dentro de Google Colab.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for beginners who seek a foundational understanding of Tensorflow
Practical application of Tensorflow through hands-on project
Introduces TensorflowJS for web-based model consumption
Course requires prior programming knowledge and familiarity with Google Colab

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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 Clasificación de imágenes con Tensorflow with these activities:
Revise basic concepts of machine learning
Retain essential knowledge and familiarize yourself with core principles of machine learning.
Show steps
  • Review lecture notes and textbooks from previous machine learning courses.
  • Complete practice problems or online quizzes to test your understanding.
Solve Tensorflow coding challenges
Enhance your Tensorflow coding skills and strengthen your understanding of algorithms.
Show steps
  • Find coding challenges or exercises online, such as on LeetCode or Kaggle.
  • Solve the challenges using Tensorflow, focusing on implementing efficient and accurate solutions.
Show all two activities

Career center

Learners who complete Clasificación de imágenes con Tensorflow will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineers develop computer vision systems, which are used in a variety of applications, such as object detection, facial recognition, and medical imaging. As a Computer Vision Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which are essential skills for success in this field.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. As a Machine Learning Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy image classification models. This course will help you build a foundation in Tensorflow and machine learning, which are essential skills for success in this field.
Data Scientist
Data Scientists use data to solve business problems. As a Data Scientist who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which are essential skills for success in this field.
Data Analyst
Data Analysts use programming to untangle complex data and develop actionable insights. As a Data Analyst who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which are essential skills for success in this field.
Robotics Engineer
Robotics Engineers design, develop, and build robots. As a Robotics Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of robotics.
Biomedical Engineer
Biomedical Engineers use engineering principles to solve problems in medicine and biology. As a Biomedical Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of biomedical engineering.
Software Engineer
Software Engineers design, develop, and maintain software systems. As a Software Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which are increasingly important skills for Software Engineers.
Electrical Engineer
Electrical Engineers design, develop, and test electrical systems. As an Electrical Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of electrical engineering.
Mechanical Engineer
Mechanical Engineers design, develop, and build mechanical systems. As a Mechanical Engineer who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of mechanical engineering.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical modeling to solve financial problems. As a Quantitative Analyst who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of financial modeling.
Product Manager
Product Managers are responsible for the development and launch of new products. As a Product Manager who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of product development.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical modeling to solve business problems. As an Operations Research Analyst who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of operations research.
Business Analyst
Business Analysts help businesses understand their data and make better decisions. As a Business Analyst who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of data analysis.
Market Research Analyst
Market Research Analysts study market trends and consumer behavior. As a Market Research Analyst who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of market research.
User Experience Researcher
User Experience Researchers study how users interact with products and services. As a User Experience Researcher who has taken this course, you will understand how to use Tensorflow to develop and deploy machine learning models for image classification tasks. This course will help you build a foundation in Tensorflow and machine learning, which can be helpful for understanding the technical aspects of user experience research.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Clasificación de imágenes con Tensorflow.
Este libro ofrece una guía práctica para el aprendizaje profundo con Python, utilizando TensorFlow. Cubre temas como redes neuronales, CNN, RNN y LSTM. Es una referencia valiosa para aquellos que buscan profundizar en el aprendizaje profundo y sus aplicaciones.
Este libro proporciona una guía práctica para el aprendizaje automático con Python, utilizando bibliotecas populares como Scikit-Learn, Keras y TensorFlow. Cubre una amplia gama de algoritmos y técnicas de aprendizaje automático.
Este libro proporciona una guía integral para el aprendizaje profundo con TensorFlow. Cubre temas avanzados como redes neuronales convolucionales, redes neuronales recurrentes y modelos generativos.
Este libro proporciona una guía práctica para el aprendizaje profundo con Python y Keras. Cubre temas como redes neuronales, CNN, RNN y LSTM. Es un recurso valioso para aquellos que buscan profundizar en el aprendizaje profundo y sus aplicaciones.
Este libro proporciona una introducción al uso de TensorFlow para la ciencia de datos. Cubre temas como la preparación de datos, el modelado de datos y la visualización de datos. Es un recurso valioso para aquellos que buscan utilizar TensorFlow para tareas de ciencia de datos.
Este libro se centra en el aprendizaje profundo para la visión por computadora, proporcionando una guía completa para desarrollar y entrenar modelos de visión por computadora con TensorFlow. Es especialmente útil para aquellos interesados en aplicaciones de visión por computadora.
Este libro utiliza ilustraciones y analogías para explicar los conceptos complejos del aprendizaje profundo. Es un recurso útil para aquellos que buscan una comprensión intuitiva del aprendizaje profundo.
Este libro ofrece una explicación intuitiva y fácil de entender sobre el aprendizaje profundo. Utiliza analogías y ejemplos prácticos para hacer que los conceptos complejos sean accesibles para los lectores.

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