This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization.
Este curso forma parte de Programa Especializado - Aprendizaje profundo
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
ofrecido por
Habilidades que obtendrás
Programa - Qué aprenderás en este curso
Practical aspects of Deep Learning
Optimization algorithms
Hyperparameter tuning, Batch Normalization and Programming Frameworks
40%
36%
11%
Principales revisiones sobre Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.
Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.
Instructores
Andrew Ng
CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
Head Teaching Assistant - Kian Katanforoosh
Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
Teaching Assistant - Younes Bensouda Mourri
Mathematical & Computational Sciences, Stanford University, deeplearning.aiAcerca de deeplearning.ai
Acerca de Programa especializado Aprendizaje profundo
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
