Informações sobre o curso
4.5
114 classificações
15 avaliações

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível avançado

Aprox. 11 horas para completar

Sugerido: 16 hours/week...

Inglês

Legendas: Inglês

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível avançado

Aprox. 11 horas para completar

Sugerido: 16 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

Working with Sequences

In this module, you’ll learn what a sequence is, see how you can prepare sequence data for modeling, and be introduced to some classical approaches to sequence modeling and practice applying them....
14 vídeos (total de (Total 41 mín.) min), 1 leitura, 4 testes
14 videos
Getting Started with Google Cloud Platform and Qwiklabs3min
Sequence data and models5min
From sequences to inputs2min
Modeling sequences with linear models2min
Lab intro: using linear models for sequences20s
Lab solution: using linear models for sequences7min
Modeling sequences with DNNs2min
Lab intro: using DNNs for sequences19s
Lab solution: using DNNs for sequences2min
Modeling sequences with CNNs3min
Lab intro: using CNNs for sequences19s
Lab solution: using CNNs for sequences3min
The variable-length problem4min
1 leituras
How to send course feedback10min
1 exercício prático
Working with Sequences
15 minutos para concluir

Recurrent Neural Networks

In this module, we introduce recurrent neural nets, explain how they address the variable-length sequence problem, explain how our traditional optimization procedure applies to RNNs, and review the limits of what RNNs can and can’t represent....
4 vídeos (total de (Total 15 mín.) min), 1 teste
4 videos
How RNNs represent the past4min
The limits of what RNNs can represent5min
The vanishing gradient problem1min
1 exercício prático
Recurrent Neural Networks
4 horas para concluir

Dealing with Longer Sequences

In this module we dive deeper into RNNs. We’ll talk about LSTMs, Deep RNNs, working with real world data, and more....
14 vídeos (total de (Total 62 mín.) min), 4 testes
14 videos
LSTMs and GRUs6min
RNNs in TensorFlow2min
Lab Intro: Time series prediction: end-to-end (rnn)45s
Lab Solution: Time series prediction: end-to-end (rnn)10min
Deep RNNs1min
Lab Intro: Time series prediction: end-to-end (rnn2)26s
Lab Solution: Time series prediction: end-to-end (rnn2)6min
Improving our Loss Function2min
Demo: Time series prediction: end-to-end (rnnN)3min
Working with Real Data10min
Lab Intro: Time Series Prediction - Temperature from Weather Data1min
Lab Solution: Time Series Prediction - Temperature from Weather Data11min
Summary1min
1 exercício prático
Dealing with Longer Sequences
Semana
2
2 horas para concluir

Text Classification

In this module we look at different ways of working with text and how to create your own text classification models. ...
8 vídeos (total de (Total 35 mín.) min), 2 testes
8 videos
Text Classification6min
Selecting a Model2min
Lab Intro: Text Classification47s
Lab Solution: Text Classification11min
Python vs Native TensorFlow4min
Demo: Text Classification with Native TensorFlow7min
Summary1min
1 exercício prático
Text Classification
1 hora para concluir

Reusable Embeddings

Labeled data for our classification models is expensive and precious. Here we will address how we can reuse pre-trained embeddings to make our models with TensorFlow Hub....
6 vídeos (total de (Total 28 mín.) min), 2 testes
6 videos
Modern methods of making word embeddings8min
Introducing TensorFlow Hub1min
Lab Intro: Evaluating a pre-trained embedding from TensorFlow Hub24s
Lab Solution: TensorFlow Hub9min
Using TensorFlow Hub within an estimator1min
1 exercício prático
Reusable Embeddings
3 horas para concluir

Encoder-Decoder Models

In this module, we focus on a sequence-to-sequence model called the encoder-decoder network to solve tasks, such as Machine Translation, Text Summarization and Question Answering....
10 vídeos (total de (Total 84 mín.) min), 3 testes
10 videos
Attention Networks4min
Training Encoder-Decoder Models with TensorFlow6min
Introducing Tensor2Tensor11min
Lab Intro: Cloud poetry: Training custom text models on Cloud ML Engine1min
Lab Solution: Cloud poetry: Training custom text models on Cloud ML Engine25min
AutoML Translation4min
Dialogflow6min
Lab Intro: Introducing Dialogflow54s
Lab Solution: Dialogflow13min
1 exercício prático
Encoder-Decoder Models
14 minutos para concluir

Summary

In this final module, we review what you have learned so far about sequence modeling for time-series and natural language data. ...
1 vídeo (total de (Total 4 mín.) min), 1 leitura
1 vídeos
1 leituras
Additional Reading10min
4.5
15 avaliaçõesChevron Right

Melhores avaliações

por JWNov 11th 2018

Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.

por MDFeb 3rd 2019

Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.

Sobre 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....

Sobre o Programa de cursos integrados Advanced Machine Learning with TensorFlow on Google Cloud Platform

>>>Look for details below for COMPLETION CHALLENGE, receive up to $150 in Qwiklabs credits<<< This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order. COMPLETION CHALLENGE For every course you complete before 11:59pm PT May 5, 2019; we will send you 30 Qwiklabs credits (upto $150 USD value)!...
Advanced Machine Learning with TensorFlow on Google Cloud Platform

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