About this Course

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Coursera Labs
Includes hands on learning projects.
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Beginner Level

We recommend completing Supervised Learning: Regression and Classification - course 1 of the Machine Learning Specialization.

Approx. 31 hours to complete
English

What you will learn

  • Build and train a neural network with TensorFlow to perform multi-class classification

  • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world

  • Build and use decision trees and tree ensemble methods, including random forests and boosted trees

Skills you will gain

  • Artificial Neural Network
  • Xgboost
  • Tensorflow
  • Tree Ensembles
  • Advice for Model Development
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs External Link
Beginner Level

We recommend completing Supervised Learning: Regression and Classification - course 1 of the Machine Learning Specialization.

Approx. 31 hours to complete
English

Offered by

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DeepLearning.AI

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Stanford University

Syllabus - What you will learn from this course

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Week
1
Week 1
7 hours to complete

Neural Networks

7 hours to complete
17 videos (Total 140 min)
Week
2
Week 2
9 hours to complete

Neural network training

9 hours to complete
14 videos (Total 134 min)
Week
3
Week 3
7 hours to complete

Advice for applying machine learning

7 hours to complete
17 videos (Total 174 min)
Week
4
Week 4
6 hours to complete

Decision trees

6 hours to complete
13 videos (Total 97 min), 1 reading, 4 quizzes

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About the Machine Learning Specialization

Machine Learning

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