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Analizando imágenes con Amazon Rekognition
Nestor Nicolas Campos Rojas
Nestor Nicolas Campos Rojas
En este proyecto, vas a implementar un modelo de clasificación de imágenes con Amazon Rekognition, a partir de datos almacenados en S3, de forma simple sin requerir conocimientos de programación o Machine Learning avanzado.
Register for this course and see more details by visiting:
OpenCourser.com/course/hqeikl/analizando
What's inside
Syllabus
Project Overview
En este proyectos, vamos a crear un modelo de visión computaciones para clasificar fotografías utilizando Amazon Rekognition.
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Know what's good ,
what to watch for , and
possible dealbreakers
Designed for individuals with no programming or advanced Machine Learning knowledge, making it accessible to a wider audience
Uses a simplified approach to image classification using Amazon Rekognition
Empowers learners with the ability to build image classification models without prior coding experience
Emphasizes practical application of image classification in the context of computer vision
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Activities
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Analizando imágenes con Amazon Rekognition.
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Career center
Learners who complete Analizando imágenes con Amazon Rekognition will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Using Amazon Rekognition to classify images is a core skill for a Computer Vision Engineer. You will use this video recognition technology and others to analyze and interpret visual data. This is extremely useful in self-driving vehicles, security systems, and medical imaging.
Data Scientist
Data Scientist
As a Data Scientist, you will gain experience using Amazon Rekognition, a cloud platform, and other AWS tools to perform machine learning tasks. In this role, you will analyze data, build models, and deploy predictive analytics.
Machine Learning Engineer
Machine Learning Engineer
For Machine Learning Engineers, Amazon Rekognition is a tool for developing models, which can be used for tasks such as image classification, object detection, and facial recognition. With it, you can build a foundation for many image-based applications.
Software Engineer
Software Engineer
As a Software Engineer, you may use Amazon Rekognition to integrate image analysis capabilities into software applications.
Business Analyst
Business Analyst
Business Analysts can utilize Amazon Rekognition to analyze market trends, identify customer needs, and optimize business processes.
UX Designer
UX Designer
UX Designers may incorporate Amazon Rekognition into their work to improve the user experience of digital products.
Product Manager
Product Manager
Product Managers may use Amazon Rekognition to analyze customer data, understand user behavior, and improve product design.
Marketing Manager
Marketing Manager
For Marketing Managers, Amazon Rekognition can be used to analyze campaign performance, target audiences, and optimize marketing strategies.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts may use Amazon Rekognition to analyze financial data, identify trends, and make predictions.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts may utilize Amazon Rekognition to analyze operational data, optimize processes, and improve efficiency.
Statistician
Statistician
Statisticians may find Amazon Rekognition useful for analyzing large datasets, identifying patterns, and drawing conclusions.
Data Architect
Data Architect
For Data Architects, Amazon Rekognition can be used to design and implement data architectures that support image analysis applications.
Database Administrator
Database Administrator
Database Administrators may utilize Amazon Rekognition to manage and optimize databases that store image data.
Systems Engineer
Systems Engineer
Systems Engineers may use Amazon Rekognition to design and implement systems that incorporate image analysis capabilities.
Technical Writer
Technical Writer
Technical Writers may use Amazon Rekognition to create documentation for image analysis systems and applications.
For more career information including salaries, visit:
OpenCourser.com/course/hqeikl/analizando
Reading list
We've selected eight 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
Analizando imágenes con Amazon Rekognition.
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Este libro de texto integral cubre los fundamentos de la visión artificial, brindando una base teórica sólida para comprender los algoritmos y técnicas utilizados en Amazon Rekognition.
Este libro práctico guía a los lectores a través de la implementación de algoritmos de aprendizaje profundo para tareas de visión artificial, lo que proporciona conocimientos valiosos para aprovechar al máximo Amazon Rekognition.
Este libro proporciona una introducción práctica al aprendizaje profundo con Python, sentando las bases para comprender los algoritmos y técnicas utilizados en Amazon Rekognition.
Este libro de texto clásico ofrece una cobertura integral del reconocimiento de patrones y el aprendizaje automático, proporcionando una base teórica para comprender los métodos de Amazon Rekognition.
Este libro fundamental ofrece una introducción integral a los métodos estadísticos utilizados en el aprendizaje automático, proporcionando una base sólida para comprender los algoritmos de Amazon Rekognition.
Esta obra clásica proporciona una base sólida en los fundamentos de la visión artificial, sentando las bases para comprender los algoritmos de Amazon Rekognition.
Este libro ofrece una introducción teórica al aprendizaje automático desde una perspectiva probabilística, proporcionando una comprensión profunda de los modelos subyacentes a Amazon Rekognition.
Esta guía práctica proporciona una descripción general de las métricas de evaluación utilizadas en la visión artificial, ayudando a los lectores a medir y mejorar el rendimiento de los modelos de Amazon Rekognition.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hqeikl/analizando
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Effort
1 hora
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Nestor Nicolas Campos Rojas
Language
Español
Good to know
Designed for individuals with no programming or advanced Machine Learning knowledge, making it accessible to a wider audience
Uses a simplified approach to image classification using Amazon Rekognition
Empowers learners with the ability to build image classification models without prior coding experience
Emphasizes practical application of image classification in the context of computer vision
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