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Challenge: Manual Hyperparameter Tuning | Conclusion
Introduction to Neural Networks
course content

Course Content

Introduction to Neural Networks

Introduction to Neural Networks

1. Concept of Neural Network
2. Neural Network from Scratch
3. Conclusion

bookChallenge: Manual Hyperparameter Tuning

Task

Until now, we have used the neural network only for the classification task. Now try to solve the regression problem using MLPRegression.

To do this, we will get the real world California Housing dataset and try to teach the model to predict median home value for households in tens of thousands of US dollars. Your goal is to have the Mean Absolute Error (MAE) be less than 0.4.

  1. Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
  2. Experiment with the number of epochs (change number of epochs from 10 to 50).
  3. Experiment with the learning rate (change it in from 0.0001 to 1).

Make sure your MAE is less than 0.4 before submitting.

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Section 3. Chapter 3
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bookChallenge: Manual Hyperparameter Tuning

Task

Until now, we have used the neural network only for the classification task. Now try to solve the regression problem using MLPRegression.

To do this, we will get the real world California Housing dataset and try to teach the model to predict median home value for households in tens of thousands of US dollars. Your goal is to have the Mean Absolute Error (MAE) be less than 0.4.

  1. Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
  2. Experiment with the number of epochs (change number of epochs from 10 to 50).
  3. Experiment with the learning rate (change it in from 0.0001 to 1).

Make sure your MAE is less than 0.4 before submitting.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 3. Chapter 3
toggle bottom row

bookChallenge: Manual Hyperparameter Tuning

Task

Until now, we have used the neural network only for the classification task. Now try to solve the regression problem using MLPRegression.

To do this, we will get the real world California Housing dataset and try to teach the model to predict median home value for households in tens of thousands of US dollars. Your goal is to have the Mean Absolute Error (MAE) be less than 0.4.

  1. Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
  2. Experiment with the number of epochs (change number of epochs from 10 to 50).
  3. Experiment with the learning rate (change it in from 0.0001 to 1).

Make sure your MAE is less than 0.4 before submitting.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Task

Until now, we have used the neural network only for the classification task. Now try to solve the regression problem using MLPRegression.

To do this, we will get the real world California Housing dataset and try to teach the model to predict median home value for households in tens of thousands of US dollars. Your goal is to have the Mean Absolute Error (MAE) be less than 0.4.

  1. Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
  2. Experiment with the number of epochs (change number of epochs from 10 to 50).
  3. Experiment with the learning rate (change it in from 0.0001 to 1).

Make sure your MAE is less than 0.4 before submitting.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 3
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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