Course Content
Introduction to Neural Networks
Introduction to Neural Networks
Challenge: 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
.
- Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
- Experiment with the number of epochs (change number of epochs from 10 to 50).
- Experiment with the learning rate (change it in from 0.0001 to 1).
Make sure your MAE is less than 0.4
before submitting.
Thanks for your feedback!
Challenge: 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
.
- Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
- Experiment with the number of epochs (change number of epochs from 10 to 50).
- Experiment with the learning rate (change it in from 0.0001 to 1).
Make sure your MAE is less than 0.4
before submitting.
Thanks for your feedback!
Challenge: 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
.
- Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
- Experiment with the number of epochs (change number of epochs from 10 to 50).
- Experiment with the learning rate (change it in from 0.0001 to 1).
Make sure your MAE is less than 0.4
before submitting.
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
.
- Experiment with the hidden layers (use 1-2 hidden layers with 10-30 neurons for each).
- Experiment with the number of epochs (change number of epochs from 10 to 50).
- Experiment with the learning rate (change it in from 0.0001 to 1).
Make sure your MAE is less than 0.4
before submitting.