Machine Learning with TensorFlow & Cloud ML
Google Cloud 2018
| Intermediate
- 14 Videos | 1h 19m 47s
- Includes Assessment
- Earns a Badge
Cloud ML combines the Google Cloud Platform with TensorFlow to create models at scale. Explore concepts behind TensorFlow and scaling, as well as training models locally and in the cloud.
WHAT YOU WILL LEARN
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describe concepts of machine learning in relation to GCPdescribe the use of datasets in GCPdemonstrate how to load a dataset for Cloud ML in GCPdescribe the use of TensorFlow with machine learningrun a TensorFlow Python program in Google Cloud Shelluse TensorFlow to run a local trainerdemonstrate how to use TensorBoard to inspect TensorFlow logs and graphs
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run a local trainer in distributed modedemonstrate how to run a single-instance trainer in the cloudinspect Stackdriver logs for an ML Engine job run in the clouddescribe the process of scaling with Cloud MLdemonstrate how to run distributed training in the clouduse hyperparameter tuning to help maximize a model's predictive accuracydescribe the TensorFlow operations that are used for big data
IN THIS COURSE
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1.Exploring Machine Learning3m 48sUP NEXT
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2.Machine Learning Datasets3m 19s
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3.Loading Datasets for Cloud ML in GCP4m 57s
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4.Understanding TensorFlow2m 40s
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5.Running a TensorFlow Python Program4m 56s
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6.Using TensorFlow to Run a Local Trainer10m 7s
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7.Using TensorBoard to Inspect Logs7m 2s
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8.Running Local Trainers in Distributed Mode4m 49s
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9.Running a Single-instance Trainer in the Cloud11m 34s
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10.Inspecting Stackdriver Logs4m 11s
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11.Understanding Cloud ML Scaling2m 23s
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12.Running Distributed Training in the Cloud4m 54s
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13.Using Hyperparameter Tuning5m 13s
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14.Exercise: Using TensorFlow and Cloud ML9m 52s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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