Este curso forma parte de Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

4.7
estrellas
4,689 calificaciones

97 %

Laurence Moroney

107.470 ya inscrito

Ofrecido Por

Certificado profesional de DeepLearning.AI desarrollador de TensorFlowdeeplearning.ai

Acerca de este Curso

110.014 vistas recientes

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data!

The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 4 de 4 en

Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

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. 23 horas para completar

Inglés (English)

Qué aprenderás

Solve time series and forecasting problems in TensorFlow
Prepare data for time series learning using best practices
Explore how RNNs and ConvNets can be used for predictions
Build a sunspot prediction model using real-world data

Habilidades que obtendrás

Forecasting
Machine Learning
Tensorflow
Time Series
prediction

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 4 de 4 en

Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

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. 23 horas para completar

Inglés (English)

Instructor

Calificación del instructor

4,73/5 (682 calificaciones)

Laurence Moroney

Instructor

Lead AI Advocate, Google

408.503 alumnos

15 cursos

Ofrecido por

deeplearning.ai

Programa - Qué aprenderás en este curso

Calificación del contenido97%(10,456 calificaciones)

Semana

Semana 1

6 horas para completar

Sequences and Prediction

Hi Learners and welcome to this course on sequences and prediction! In this course we'll take a look at some of the unique considerations involved when handling sequential time series data -- where values change over time, like the temperature on a particular day, or the number of visitors to your web site. We'll discuss various methodologies for predicting future values in these time series, building on what you've learned in previous courses!

6 horas para completar

10 videos (Total 32 minutos), 6 lecturas, 4 cuestionarios

10 videos

Introduction, A conversation with Andrew Ng3m

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 windows50s

Forecasting3m

6 lecturas

Where to find the notebooks for this course5m

Introduction to time series notebook (Lab 1)30m

Forecasting notebook (Lab 2)30m

Week 1 Wrap up2m

Assignment Troubleshooting Tips5m

(Optional) Downloading your Notebook and Refreshing your Workspace2m

1 ejercicio de práctica

Week 1 Quiz30m

Semana

Semana 2

6 horas para completar

Deep Neural Networks for Time Series

6 horas para completar

10 videos (Total 25 minutos), 4 lecturas, 3 cuestionarios

10 videos

A conversation with Andrew Ng1m

Preparing features and labels4m

Preparing features and labels (screencast)2m

Feeding windowed dataset into neural network2m

Single layer neural network2m

Machine learning on time windows37s

Prediction2m

Recurrent Neural Networks for Time Series

5 horas para completar

8 videos (Total 17 minutos), 5 lecturas, 3 cuestionarios

Semana

Semana 4

7 horas para completar

Real-world time series data

7 horas para completar

11 videos (Total 23 minutos), 9 lecturas, 3 cuestionarios

11 videos

Week 4 - A conversation with Andrew Ng1m

Convolutions58s

Bi-directional LSTMs3m

Convolutions with LSTM1m

Real data - sunspots3m

Train and tune the model2m

Prediction1m

Sunspots1m

Combining our tools for analysis3m

Congratulations!38s

Specialization wrap up - A conversation with Andrew Ng2m

9 lecturas

Convolutional neural networks course10m

Reseñas

4.7

746 reseña

5 stars
76,83 %
4 stars
16,58 %
3 stars
4,07 %
2 stars
1,23 %
1 star
1,27 %

Principales reseñas sobre SEQUENCES, TIME SERIES AND PREDICTION

por SP26 de mar. de 2020

Few hands on programming assignments could be better for experience as was the case with starting two courses. Overall good course and the structure was well laid. Thanks for building it up

por AK4 de jun. de 2020

Laurence Moroney is the best. Before taking up the course, i didnt know anything about the AI or ML or Tensorflow. The concepts were explained in such a manner that anyone can learn Tensorflow.

por SW15 de sep. de 2020

Great course for review and hands-on practice of RNN/LSTM/DNN after AI specialization (Sequence Models). However, without background of DL (sequence models) it's a bit hard to catch up.

por MB8 de jul. de 2020

An exceptional course design to enable practicing with ready code and teaching what actually runs in LSTM / DNN models. With this momentum, anyone will continue on another course.

Ver todas las reseñas

Acerca de Certificado profesional de DeepLearning.AI desarrollador de TensorFlow

TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.

In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate. Ready to deploy your models to the world? Learn how to go live with your models with the TensorFlow: Data and Deployment Specialization. Looking to customize and build powerful real-world models for complex scenarios? Check out the TensorFlow: Advanced Techniques Specialization.

DeepLearning.AI desarrollador de TensorFlow

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Certificado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos del Certificado 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.

¿Tienes más preguntas? Visita el Centro de Ayuda al Estudiante.

Sequences, Time Series and Prediction

Acerca de este Curso

Qué aprenderás

Habilidades que obtendrás