Зміст курсу
Introduction to Neural Networks
Introduction to Neural Networks
Manual Hyperparameter Tuning
Завдання
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.
Завдання
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.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівВсе було зрозуміло?
Manual Hyperparameter Tuning
Завдання
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.
Завдання
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.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівВсе було зрозуміло?
Manual Hyperparameter Tuning
Завдання
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.
Завдання
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.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівВсе було зрозуміло?
Завдання
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.
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів