Acerca de este Curso
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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 intermedio

You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

Aprox. 8 horas para completar

Sugerido: 4 weeks of study, 4-5 hours/week...

Inglés (English)

Subtítulos: Inglés (English)
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Machine Learning Engineers
  • Traders
  • Data Engineers
  • Chief Technology Officers (CTOs)

Qué aprenderás

  • Check

    Solve time series and forecasting problems in TensorFlow

  • Check

    Prepare data for time series learning using best practices

  • Check

    Explore how RNNs and ConvNets can be used for predictions

  • Check

    Build a sunspot prediction model using real-world data

Habilidades que obtendrás

ForecastingMachine LearningTensorflowTime Seriesprediction
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Machine Learning Engineers
  • Traders
  • Data Engineers
  • Chief Technology Officers (CTOs)

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 intermedio

You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

Aprox. 8 horas para completar

Sugerido: 4 weeks of study, 4-5 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
3 horas para completar

Sequences and Prediction

10 videos (Total 33 minutos), 3 lecturas, 3 cuestionarios
10 videos
Time series examples4m
Machine learning applied to time series1m
Common patterns in time series5m
Introduction to time series4m
Train, validation and test sets3m
Metrics for evaluating performance2m
Moving average and differencing2m
Trailing versus centered windows1m
Forecasting4m
3 lecturas
Introduction to time series notebook10m
Forecasting notebook10m
Week 1 Wrap up10m
1 ejercicios de práctica
Week 1 Quiz
Semana
2
3 horas para completar

Deep Neural Networks for Time Series

10 videos (Total 27 minutos), 5 lecturas, 3 cuestionarios
10 videos
Preparing features and labels4m
Preparing features and labels3m
Feeding windowed dataset into neural network2m
Single layer neural network2m
Machine learning on time windows37s
Prediction2m
More on single layer neural network2m
Deep neural network training, tuning and prediction4m
Deep neural network3m
5 lecturas
Preparing features and labels notebook10m
Sequence bias10m
Single layer neural network notebook10m
Deep neural network notebook10m
Week 2 Wrap up10m
1 ejercicios de práctica
Week 2 Quiz
Semana
3
3 horas para completar

Recurrent Neural Networks for Time Series

10 videos (Total 20 minutos), 5 lecturas, 3 cuestionarios
10 videos
Conceptual overview2m
Shape of the inputs to the RNN2m
Outputting a sequence1m
Lambda layers1m
Adjusting the learning rate dynamically2m
RNN1m
LSTM1m
Coding LSTMs2m
More on LSTM1m
5 lecturas
More info on Huber loss10m
RNN notebook10m
Link to the LSTM lesson10m
LSTM notebook10m
Week 3 Wrap up10m
1 ejercicios de práctica
Week 3 Quiz
Semana
4
3 horas para completar

Real-world time series data

11 videos (Total 24 minutos), 5 lecturas, 3 cuestionarios
11 videos
Convolutions58s
Bi-directional LSTMs3m
LSTM1m
Real data - sunspots3m
Train and tune the model3m
Prediction1m
Sunspots1m
Combining our tools for analysis3m
Congratulations!38s
Specialization wrap up - A conversation with Andrew Ng2m
5 lecturas
Convolutional neural networks course10m
More on batch sizing10m
LSTM notebook10m
Sunspots notebook10m
Wrap up10m
1 ejercicios de práctica
Week 4 Quiz
4.6
78 revisionesChevron Right

Principales revisiones sobre Sequences, Time Series and Prediction

por ORAug 4th 2019

It was an amazing experience to learn from such great experts in the field and get a complete understanding of all the concepts involved and also get thorough understanding of the programming skills.

por MKAug 3rd 2019

This was really a beautifully designed course. They didn't focused on teaching too much of thing at once but build up the base slowly and strongly for better understanding.

Instructores

Avatar

Laurence Moroney

AI Advocate
Google Brain

Acerca de deeplearning.ai

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

Acerca de Programa especializado TensorFlow in Practice

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Courses 1-3 are available now, with Course 4 launching in July....
TensorFlow in Practice

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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