Describir las técnicas de Deep Learning utilizando TensorFlow y Keras para resolver problemas de reconocimiento de patrones y generación de texto.
Add to your LinkedIn profile
March 2025
27 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
En esta sección, los estudiantes serán introducidos al mundo del Deep Learning, comenzando con una explicación de las redes neuronales artificiales. Se explorarán los componentes y la estructura de las NN, y se realizará un primer proyecto práctico de programación para reconocer dígitos manuscritos.
13 videos1 reading11 assignments
Esta sección se centra en el uso de TensorFlow y Keras para la construcción y entrenamiento de redes neuronales. Los estudiantes aprenderán a implementar modelos para la detección de dígitos manuscritos y el diagnóstico de cáncer de mama, utilizando estas poderosas herramientas de Deep Learning
10 videos2 readings6 assignments
Explorarás las redes neuronales convolucionales (CNN), una técnica avanzada para el procesamiento de imágenes. Se desarrollarán proyectos prácticos para el reconocimiento de términos manuscritos y el lenguaje de señas, aprendiendo a guardar, cargar y compartir los modelos de redes neuronales.
14 videos1 reading8 assignments
Esta sección se dedica a las redes neuronales recurrentes (RNN) y las Long Short-Term Memory (LSTM), utilizadas principalmente para la generación de texto. Los contenidos de está sección te permitirán comprender cómo crear modelos que generen texto de manera coherente, practicando con ejemplos y ejercicios específicos.
8 videos3 readings2 assignments
Illinois Tech
DeepLearning.AI
Coursera Project Network
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
