Informações sobre o curso

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consegui um benefício significativo de carreira com este curso

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Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 6 horas para completar
Inglês
Legendas: Francês, Português (Brasil), Alemão, Inglês, Espanhol, Japonês...

Habilidades que você terá

TensorflowBigqueryMachine LearningData Cleansing

Resultados de carreira do aprendiz

43%

comecei uma nova carreira após concluir estes cursos

44%

consegui um benefício significativo de carreira com este curso

29%

recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 6 horas para completar
Inglês
Legendas: Francês, Português (Brasil), Alemão, Inglês, Espanhol, Japonês...

Instrutores

oferecido por

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Google Cloud

Programa - O que você aprenderá com este curso

Classificação do conteúdoThumbs Up92%(2,809 classificações)Info
Semana
1

Semana 1

9 minutos para concluir

Introduction

9 minutos para concluir
2 vídeos (Total 9 mín.)
2 videos
Intro to Qwiklabs5min
1 hora para concluir

Practical ML

1 hora para concluir
10 vídeos (Total 62 mín.)
10 videos
Supervised Learning5min
Regression and Classification11min
Short History of ML: Linear Regression7min
Short History of ML: Perceptron5min
Short History of ML: Neural Networks7min
Short History of ML: Decision Trees5min
Short History of ML: Kernel Methods4min
Short History of ML: Random Forests4min
Short History of ML: Modern Neural Networks8min
1 exercício prático
Module Quiz6min
1 hora para concluir

Optimization

1 hora para concluir
13 vídeos (Total 60 mín.)
13 videos
Defining ML Models4min
Introducing the Natality Dataset6min
Introducing Loss Functions6min
Gradient Descent5min
Troubleshooting a Loss Curve2min
ML Model Pitfalls6min
Lab: Introducing the TensorFlow Playground6min
Lab: TensorFlow Playground - Advanced3min
Lab: Practicing with Neural Networks6min
Loss Curve Troubleshooting1min
Performance Metrics3min
Confusion Matrix5min
1 exercício prático
Module Quiz6min
3 horas para concluir

Generalization and Sampling

3 horas para concluir
9 vídeos (Total 64 mín.)
9 videos
Generalization and ML Models6min
When to Stop Model Training5min
Creating Repeatable Samples in BigQuery6min
Demo: Splitting Datasets in BigQuery8min
Lab Introduction1min
Lab Solution Walkthrough9min
Lab Introduction2min
Lab Solution Walkthrough23min
1 exercício prático
Module Quiz12min
3 minutos para concluir

Summary

3 minutos para concluir
1 vídeo (Total 3 mín.)
1 vídeos

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Sobre Programa de cursos integrados 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

Perguntas Frequentes – FAQ

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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