We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-performance predictions using Cloud Machine Learning Engine.
Este curso faz parte do Programa de cursos integrados Machine Learning with TensorFlow on Google Cloud Platform
Intro to TensorFlow
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Habilidades que você terá
Application Programming Interfaces (API)EstimatorMachine LearningTensorflowCloud Computing
Resultados de carreira do aprendiz
33%
comecei uma nova carreira após concluir estes cursos
38%
consegui um benefício significativo de carreira com este curso
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Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 10 horas para completar
Sugerido: 2-3 weeks of study, 8-10 hours/week
Inglês
Legendas: Francês, Português (Brasil), Alemão, Inglês, Espanhol, Japonês
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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.
Programa - O que você aprenderá com este curso
7 minutos para concluir
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.
7 minutos para concluir
2 vídeos (Total 7 mín.)
3 horas para concluir
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.
3 horas para concluir
19 vídeos (Total 72 mín.)
19 videos
Introduction1min
What is TensorFlow2min
Benefits of a Directed Graph5min
TensorFlow API Hierarchy3min
Lazy Evaluation4min
Graph and Session4min
Evaluating a Tensor2min
Visualizing a graph2min
Tensors6min
Variables6min
Lab Intro: Writing low-level TensorFlow programs16s
Lab Solution8min
Introduction5min
Shape problems3min
Fixing shape problems2min
Data type problems1min
Debugging full programs4min
Intro: Debugging full programs15s
Demo: Debugging Full Programs3min
3 exercícios práticos
What is TensorFlow?2min
Graphs and Sessions8min
Core TensorFlow20min
4 horas para concluir
Estimator API
In this module we will walk you through the Estimator API.
4 horas para concluir
18 vídeos (Total 67 mín.)
18 videos
Introduction1min
Estimator API3min
Pre-made Estimators5min
Demo: Housing Price Model1min
Checkpointing1min
Training on in-memory datasets2min
Lab Intro: Estimator API39s
Lab Solution: Estimator API10min
Train on large datasets with Dataset API8min
Lab Intro: Scaling up TensorFlow ingest using batching35s
Lab Solution: Scaling up TensorFlow ingest using batching5min
Big jobs, Distributed training6min
Monitoring with TensorBoard3min
Demo: TensorBoard UI28s
Serving Input Function5min
Recap: Estimator API1min
Lab Intro: Creating a distributed training TensorFlow model with Estimator API51s
Lab Solution: Creating a distributed training TensorFlow model with Estimator API7min
1 exercício prático
Estimator API18min
2 horas para concluir
Scaling TensorFlow models
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.
2 horas para concluir
6 vídeos (Total 29 mín.), 1 leitura, 2 testes
6 videos
Introduction31s
Why Cloud AI Platform?6min
Train a Model2min
Monitoring and Deploying Training Jobs2min
Lab Intro: Scaling TensorFlow with Cloud AI Platform50s
Lab Solution: Scaling TensorFlow with Cloud AI Platform16min
1 leituras
Cloud ML Engine is now Cloud AI Platform10min
1 exercício prático
Cloud AI Platform10min
2 minutos para concluir
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.
2 minutos para concluir
1 vídeo (Total 2 mín.)
1 vídeos
Summary2min
Avaliações
Principais avaliações do INTRO TO TENSORFLOW
por LLAug 30, 2019
The tools and methods presented were great. The instructors were also fantastic.\n\nHowever the coding exercises were lacking in guidance even though the complete solution is given in the video.
por DWOct 16, 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 TWMar 30, 2020
This needs some updating - looks like the Tensorboard is no longer accessed in the same way as it was when this course was produced.\n\nOtherwise great! Good challenges! :/
por YGApr 4, 2019
The procedure to connect to the cloud datalab was time consuming to do it every time.\n\nSuggestion : More topics in Core Tensorflow could be added. I enjoyed the course!
por SSJun 5, 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.
por MKMar 8, 2020
The course covers quite a few concepts -- TF basics, TF estimator, Google Cloud ML. It would be easier if the material is split into TF and Google Cloud lessons.
por TBOct 6, 2018
Great course as an introduction to TF, however, the labs are not as in depth as I'd have liked. Nonetheless, the course is well executed by the presenters.
por AHAug 10, 2018
Pretty helpful in getting to know the various levels of abstractions of tensorflow API and avoiding various pitfalls while building the Tensorflow model
por SRJun 14, 2018
very useful for getting up to speed on tensorflowa little inconvenient that you have to start the infrastructure for each lab, takes minutes (5-7)
por MRJan 6, 2019
Excellent course!!! It is the best way to really understand TensorFlow and getting to know its real potential. Thanks to all the instructors!!!
por PSAug 5, 2019
Course is Best so far i learnt in Tensor Flow . It has all modules and content to be successful in Deep Learning and GCP Machine learning .
por PRDec 26, 2018
Amazing course! The short length of videos makes it lot easier for students to follow! Google is honestly the best at whatever it does! :)
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.
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