About this Course

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Learner Career Outcomes

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Flexible deadlines
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Intermediate Level
Approx. 12 hours to complete
English

What you will learn

  • Generalize a ML model using Regularization techniques

  • Tune batch size and learning rate for better model performance

  • Optimize a ML model

  • Apply the concepts in TensorFlow code

Skills you will gain

TensorflowMachine LearningCloud ComputingEstimator

Learner Career Outcomes

41%

started a new career after completing these courses

45%

got a tangible career benefit from this course

19%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 12 hours to complete
English

Instructor

Offered by

Placeholder

Google Cloud

Syllabus - What you will learn from this course

Content RatingThumbs Up83%(1,432 ratings)Info
Week
1

Week 1

3 minutes to complete

Introduction

3 minutes to complete
1 video (Total 3 min)
1 video
2 hours to complete

The Art of ML

2 hours to complete
10 videos (Total 29 min)
10 videos
Regularization4m
L1 & L2 Regularizations4m
Lab Intro: Regularization12s
Lab: Regularization2m
Learning rate and batch size5m
Optimization1m
Practicing with Tensorflow code1m
Lab Intro: Hand-Tuning ML Models18s
Lab Solution: Hand-Tuning ML Models7m
2 practice exercises
Art of ML30m
Learning Rate and Batch Size30m
2 hours to complete

Hyperparameter Tuning

2 hours to complete
5 videos (Total 8 min)
5 videos
Parameters vs Hyperparameters2m
Think Beyond Grid Search3m
Lab Intro: Improve model accuracy by Hyperparameter Tuning23s
Lab Solution: Improve model accuracy by Hyperparameter Tuning with Cloud AI Platform30s
1 practice exercise
Hyperparameter Tuning30m
Week
2

Week 2

1 hour to complete

A pinch of science

1 hour to complete
5 videos (Total 28 min)
5 videos
Regularization for sparsity5m
Lab: L1 Regularization3m
Lab Solution: L1 Regularization51s
Logistic Regression17m
2 practice exercises
L1 Regularization30m
Logistic Regression30m
3 hours to complete

The science of neural networks

3 hours to complete
6 videos (Total 70 min)
6 videos
Neural Networks18m
Lab: Neural Networks Playground12m
Training Neural Networks14m
Lab: Using Neural Networks to build a ML model11m
Multi-class Neural Networks10m
2 practice exercises
Training Neural Networks30m
Multi-class Neural Networks30m
Week
3

Week 3

1 hour to complete

Embeddings

1 hour to complete
7 videos (Total 31 min)
7 videos
Review of Embeddings5m
Recommendations4m
Data-driven Embeddings3m
Sparse Tensors4m
Train an Embedding4m
Similarity Property7m
1 practice exercise
Embeddings30m
2 hours to complete

Custom Estimator

2 hours to complete
5 videos (Total 30 min)
5 videos
Model Function6m
Lab Intro: Implementing a Custom Estimator11m
Keras Models4m
Demo: Keras Models + Estimator2m
1 practice exercise
Custom Estimator30m
5 minutes to complete

Summary

5 minutes to complete
2 videos (Total 5 min)
2 videos
Specialization Summary2m

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About the Machine Learning with TensorFlow on Google Cloud Platform Specialization

Machine Learning with TensorFlow on Google Cloud Platform

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