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Please enable JavaScript in your browser settings or update your browser.Challenge: Manual Hyperparameter Tuning | Conclusion
Introduction to Neural Networks
course content

Conteúdo do Curso

Introduction to Neural Networks

Introduction to Neural Networks

1. Concept of Neural Network
What is a Neural Network?Neural Network StructureWhat is a Neuron?Activation FunctionsForward and Backward PropagationApplications of Deep Learning in the Real World
2. Neural Network from Scratch
Single Neuron ImplementationPerceptron LayersForward PropagationBackward PropagationData PreprocessingModel Training and EvaluationNeural Network with scikit-learn
3. Conclusion
Neural Networks or Traditional ModelsOther types of Neural NetworksChallenge: Manual Hyperparameter TuningChallenge: Automatic Hyperparameter TuningQuiz: ConclusionSummary

bookChallenge: Manual Hyperparameter Tuning

Tarefa

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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 3
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bookChallenge: Manual Hyperparameter Tuning

Tarefa

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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 3
toggle bottom row

bookChallenge: Manual Hyperparameter Tuning

Tarefa

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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Tarefa

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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 3
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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