Acerca de este Curso
4.5
933 calificaciones
107 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. 7 horas para completar

Sugerido: 5 - 7 hours per week...
Idiomas disponibles

Inglés (English)

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

Habilidades que obtendrás

TensorflowBigqueryMachine LearningData Cleansing
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. 7 horas para completar

Sugerido: 5 - 7 hours per 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
9 minutos para completar

Introduction

In this course you’ll get foundational ML knowledge so that you understand the terminology that we use throughout the specialization. You will also learn practical tips and pitfalls from ML practitioners here at Google and walk away with the code and the knowledge to bootstrap your own ML models....
Reading
2 videos (Total: 9 min)
Video2 videos
Intro to Qwiklabs5m
Horas para completar
1 hora para completar

Practical ML

In this module, we will introduce some of the main types of machine learning and review the history of ML leading up to the state of the art so that you can accelerate your growth as an ML practitioner....
Reading
10 videos (Total: 62 min), 1 quiz
Video10 videos
Supervised Learning5m
Regression and Classification11m
Short History of ML: Linear Regression7m
Short History of ML: Perceptron5m
Short History of ML: Neural Networks7m
Short History of ML: Decision Trees5m
Short History of ML: Kernel Methods4m
Short History of ML: Random Forests4m
Short History of ML: Modern Neural Networks8m
Quiz1 ejercicio de práctica
Module Quiz6m
Horas para completar
1 hora para completar

Optimization

In this module we will walk you through how to optimize your ML models....
Reading
13 videos (Total: 61 min), 1 quiz
Video13 videos
Defining ML Models4m
Introducing the Natality Dataset6m
Introducing Loss Functions6m
Gradient Descent5m
Troubleshooting a Loss Curve2m
ML Model Pitfalls6m
Lab: Introducing the TensorFlow Playground6m
Lab: TensorFlow Playground - Advanced3m
Lab: Practicing with Neural Networks6m
Loss Curve Troubleshooting1m
Performance Metrics3m
Confusion Matrix5m
Quiz1 ejercicio de práctica
Module Quiz6m
Horas para completar
3 horas para completar

Generalization and Sampling

Now it’s time to answer a rather weird question: when is the most accurate ML model not the right one to pick? As we hinted at in the last module on Optimization -- simply because a model has a loss metric of 0 for your training dataset does not mean it will perform well on new data in the real world. ...
Reading
9 videos (Total: 64 min), 3 quizzes
Video9 videos
Generalization and ML Models6m
When to Stop Model Training5m
Creating Repeatable Samples in BigQuery6m
Demo: Splitting Datasets in BigQuery8m
Lab Introduction1m
Lab Solution Walkthrough9m
Lab Introduction2m
Lab Solution Walkthrough23m
Quiz1 ejercicio de práctica
Module Quiz12m
Horas para completar
3 minutos para completar

Summary

...
Reading
1 video (Total: 3 min)
Video1 video
4.5
107 revisionesChevron Right

Principales revisiones

por PAAug 4th 2018

Good course, covering all the basics about machine learning and most importantly, everything that surrounds an ml project and you need to take into account to make your ml project successful.

por ESApr 29th 2018

The technical knowledge is introduced very progressively. You understand the historic evolution and practical usage of models. Great content!

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

> 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 < *Look for details below for COMPLETION CHALLENGE, receive a GCP t-shirt!* 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. Complete any GCP specialization from now through November 30, 2018 for an opportunity to receive a GCP t-shirt (while supplies last). See forums for details....
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

  • Si decides inscribirte en el curso antes de la fecha de inicio de la sesión, tendrás acceso a todos los videos y las lecturas de la lección para el curso. Podrás enviar tareas en cuanto comience la sesión.

  • Una vez que te inscribes y comienza la sesión, tendrás acceso a todos los videos y otros recursos, incluidos artículos de lectura y el foro de debate del curso. Podrás ver y enviar tareas de práctica y completar tareas con calificación obligatorias para obtener un título y un Certificado de curso

  • Si completas el curso de manera correcta, tu Certificado de curso electrónico se agregará a la página Logros. Desde allí, puedes imprimir tu Certificado de curso o agregarlo a tu perfil de LinkedIn

  • 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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