Acerca de este Curso

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Resultados profesionales del estudiante

41%

comenzó una nueva carrera después de completar estos cursos

37%

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

12%

consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Chino (simplificado), Portugués (de Brasil), Coreano, Turco (Turkish), Inglés (English), Español (Spanish)...

Habilidades que obtendrás

HyperparameterTensorflowHyperparameter OptimizationDeep Learning

Resultados profesionales del estudiante

41%

comenzó una nueva carrera después de completar estos cursos

37%

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

12%

consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Chino (simplificado), Portugués (de Brasil), Coreano, Turco (Turkish), Inglés (English), Español (Spanish)...

ofrecido por

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deeplearning.ai

Programa - Qué aprenderás en este curso

Calificación del contenidoThumbs Up96%(46,084 calificaciones)Info
Semana
1

Semana 1

8 horas para completar

Practical aspects of Deep Learning

8 horas para completar
15 videos (Total 131 minutos), 3 lecturas, 4 cuestionarios
15 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
3 lecturas
Clarification about Upcoming Regularization Video1m
Clarification about Upcoming Understanding dropout Video1m
Clarification about Upcoming Normalizing Inputs Video1m
1 ejercicio de práctica
Practical aspects of deep learning30m
Semana
2

Semana 2

5 horas para completar

Optimization algorithms

5 horas para completar
11 videos (Total 92 minutos), 2 lecturas, 2 cuestionarios
11 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
2 lecturas
Clarification about Upcoming Adam Optimization Video1m
Clarification about Learning Rate Decay Video1m
1 ejercicio de práctica
Optimization algorithms30m
Semana
3

Semana 3

5 horas para completar

Hyperparameter tuning, Batch Normalization and Programming Frameworks

5 horas para completar
11 videos (Total 104 minutos), 2 lecturas, 2 cuestionarios
11 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
2 lecturas
Clarifications about Upcoming Softmax Video1m
Note about TensorFlow 1 and TensorFlow 210m
1 ejercicio de práctica
Hyperparameter tuning, Batch Normalization, Programming Frameworks30m

Revisiones

Principales revisiones sobre IMPROVING DEEP NEURAL NETWORKS: HYPERPARAMETER TUNING, REGULARIZATION AND OPTIMIZATION

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Acerca de Programa especializado: Aprendizaje profundo

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....
Aprendizaje profundo

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