Acerca de este Curso
4.5
771 calificaciones
85 revisiones
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 intermedio

Nivel intermedio

Horas para completar

Aprox. 9 horas para completar

Sugerido: 2-3 weeks of study, 8-10 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Francés (French), Portugués (de Brasil), Alemán (German), Español (Spanish), Japonés...

Habilidades que obtendrás

Application Programming Interfaces (API)EstimatorMachine LearningTensorflowCloud Computing
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 intermedio

Nivel intermedio

Horas para completar

Aprox. 9 horas para completar

Sugerido: 2-3 weeks of study, 8-10 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Francés (French), Portugués (de Brasil), Alemán (German), Español (Spanish), Japonés...

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
7 minutos para completar

Introduction

The tool we will use to write machine learning programs is TensorFlow and so in this course, we will introduce you to TensorFlow. In the first course, you learned how to formulate business problems as machine learning problems and in the second course, you learned how machine works in practice and how to create datasets that you can use for machine learning. Now that you have the data in place, you are ready to get started writing machine learning programs....
Reading
2 videos (Total 7 minutos)
Video2 videos
Intro to Qwiklabs5m
Horas para completar
3 horas para completar

Core TensorFlow

We will introduce you to the core components of TensorFlow and you will get hands-on practice building machine learning programs. You will compare and write lazy evaluation and imperative programs, work with graphs, sessions, variables, as finally debug TensorFlow programs....
Reading
19 videos (Total 72 minutos), 4 quizzes
Video19 videos
What is TensorFlow2m
Benefits of a Directed Graph5m
TensorFlow API Hierarchy3m
Lazy Evaluation4m
Graph and Session4m
Evaluating a Tensor2m
Visualizing a graph2m
Tensors6m
Variables6m
Lab Intro: Writing low-level TensorFlow programs16s
Lab Solution8m
Introduction5m
Shape problems3m
Fixing shape problems2m
Data type problems1m
Debugging full programs4m
Intro: Debugging full programs15s
Demo: Debugging Full Programs3m
Quiz3 ejercicios de práctica
What is TensorFlow?2m
Graphs and Sessions8m
Core TensorFlow20m
Semana
2
Horas para completar
4 horas para completar

Estimator API

In this module we will walk you through the Estimator API....
Reading
18 videos (Total 67 minutos), 4 quizzes
Video18 videos
Estimator API3m
Pre-made Estimators5m
Demo: Housing Price Model1m
Checkpointing1m
Training on in-memory datasets2m
Lab Intro: Estimator API39s
Lab Solution: Estimator API10m
Train on large datasets with Dataset API8m
Lab Intro: Scaling up TensorFlow ingest using batching35s
Lab Solution: Scaling up TensorFlow ingest using batching5m
Big jobs, Distributed training6m
Monitoring with TensorBoard3m
Demo: TensorBoard UI28s
Serving Input Function5m
Recap: Estimator API1m
Lab Intro: Creating a distributed training TensorFlow model with Estimator API51s
Lab Solution: Creating a distributed training TensorFlow model with Estimator API7m
Quiz1 ejercicio de práctica
Estimator API18m
Semana
3
Horas para completar
2 horas para completar

Scaling TensorFlow models with CMLE

I’m here to talk about how you would go about taking your TensorFlow model and training it on GCP’s managed infrastructure for machine learning model training and deployed....
Reading
6 videos (Total 29 minutos), 2 quizzes
Video6 videos
Why Cloud Machine Learning Engine?6m
Train a Model2m
Monitoring and Deploying Training Jobs2m
Lab Intro: Scaling TensorFlow with Cloud Machine Learning Engine50s
Lab Solution: Scaling TensorFlow with Cloud Machine Learning Engine16m
Quiz1 ejercicio de práctica
Cloud MLE10m
Horas para completar
2 minutos para completar

Summary

Here we summarize the TensorFlow topics we covered so far in this course. We'll revisit core TensorFlow code, the Estimator API, and end with scaling your machine learning models with Cloud Machine Learning Engine....
Reading
1 video (Total 2 minutos)
Video1 video
4.5
85 revisionesChevron Right

Principales revisiones

por DWOct 17th 2018

pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!

por SSJun 6th 2018

Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.

Acerca de Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

Acerca del programa especializado Machine Learning with TensorFlow on Google Cloud Platform

What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform. > By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <...
Machine Learning with TensorFlow on Google Cloud Platform

Preguntas Frecuentes

  • Sí, puedes acceder a una vista preliminar del primer video y ver el programa antes de inscribirte. Debes comprar el curso para acceder a contenido que no está incluido en la vista preliminar

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  • Este curso es uno de los pocos que se ofrecen en Coursera que está actualmente disponible solo para estudiantes que pagaron o que recibieron ayuda económica. / Si deseas tomar este curso, pero no puedes pagar la tarifa, te sugerimos enviar una solicitud de ayuda económica.

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