Acerca de este Curso
4.9
26,318 calificaciones
2,959 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel principiante

Nivel principiante

Horas para completar

Aprox. 14 horas para completar

Sugerido: 3 weeks, 3-6 hours per week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Chino (tradicional), Chino (simplificado), Coreano, Turco (Turkish)

Habilidades que obtendrás

HyperparameterTensorflowHyperparameter OptimizationDeep Learning
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel principiante

Nivel principiante

Horas para completar

Aprox. 14 horas para completar

Sugerido: 3 weeks, 3-6 hours per week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Chino (tradicional), Chino (simplificado), Coreano, Turco (Turkish)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
8 horas para completar

Practical aspects of Deep Learning

...
Reading
15 videos (Total 131 minutos), 4 quizzes
Video15 videos
Bias / Variance8m
Basic Recipe for Machine Learning6m
Regularization9m
Why regularization reduces overfitting?7m
Dropout Regularization9m
Understanding Dropout7m
Other regularization methods8m
Normalizing inputs5m
Vanishing / Exploding gradients6m
Weight Initialization for Deep Networks6m
Numerical approximation of gradients6m
Gradient checking6m
Gradient Checking Implementation Notes5m
Yoshua Bengio interview25m
Quiz1 ejercicio de práctica
Practical aspects of deep learning20m
Semana
2
Horas para completar
4 horas para completar

Optimization algorithms

...
Reading
11 videos (Total 92 minutos), 2 quizzes
Video11 videos
Understanding mini-batch gradient descent11m
Exponentially weighted averages5m
Understanding exponentially weighted averages9m
Bias correction in exponentially weighted averages4m
Gradient descent with momentum9m
RMSprop7m
Adam optimization algorithm7m
Learning rate decay6m
The problem of local optima5m
Yuanqing Lin interview13m
Quiz1 ejercicio de práctica
Optimization algorithms20m
Semana
3
Horas para completar
5 horas para completar

Hyperparameter tuning, Batch Normalization and Programming Frameworks

...
Reading
11 videos (Total 104 minutos), 2 quizzes
Video11 videos
Using an appropriate scale to pick hyperparameters8m
Hyperparameters tuning in practice: Pandas vs. Caviar6m
Normalizing activations in a network8m
Fitting Batch Norm into a neural network12m
Why does Batch Norm work?11m
Batch Norm at test time5m
Softmax Regression11m
Training a softmax classifier10m
Deep learning frameworks4m
TensorFlow16m
Quiz1 ejercicio de práctica
Hyperparameter tuning, Batch Normalization, Programming Frameworks20m
4.9
2,959 revisionesChevron Right
Dirección de la carrera

36%

comenzó una nueva carrera después de completar estos cursos
Beneficio de la carrera

32%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

Principales revisiones

por CVDec 24th 2017

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.

por PGOct 31st 2017

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.

Instructores

Avatar

Andrew Ng

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
Avatar

Head Teaching Assistant - Kian Katanforoosh

Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
Avatar

Teaching Assistant - Younes Bensouda Mourri

Mathematical & Computational Sciences, Stanford University, deeplearning.ai

Acerca de deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

Acerca del programa especializado Deep Learning

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI....
Deep Learning

Preguntas Frecuentes

  • 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.

  • 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.

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