Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.
Ce cours fait partie de la Spécialisation TensorFlow: Data and Deployment
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À propos de ce cours
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
Ce que vous allez apprendre
Perform efficient ETL tasks using Tensorflow Data Services APIs
Construct train/validation/test splits of any dataset - either custom or present in TensorFlow Hub Dataset library - using Splits API
Use different modules and functions of the TFDS API to prepare your data for training pipelines
Identify bottlenecks in your input pipelines and increase your workflow efficiency by input parallelization
Compétences que vous acquerrez
- Artificial Neural Network
- Tensorflow
- Extraction, Transformation And Loading (ETL)
- Data Pipelines
- TensorFlow Datasets
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
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Programme de cours : ce que vous apprendrez dans ce cours
Data Pipelines with TensorFlow Data Services
Splits and Slices API for Datasets in TF
Exporting Your Data into the Training Pipeline
Performance
Avis
- 5 stars64,64 %
- 4 stars19,73 %
- 3 stars8,89 %
- 2 stars4,12 %
- 1 star2,60 %
Meilleurs avis pour DATA PIPELINES WITH TENSORFLOW DATA SERVICES
I understand why most of the students are furious about, but content wise, it one of those extremely helpful and important courses in Coursera. Really loved it!
Excellent course both for Data Scientists and Machine Learning Engineers!
Excellent content, but the design of Exercise 4 tainted the experience somewhat by the end.
I was really looking forward to learning efficient data pipelines and that is utterly what I learned here in this course. Best in its class.
À propos du Spécialisation TensorFlow: Data and Deployment

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