ICP Deep Learning 1

OBJECTIVE:

To implement Deep Learning programming on keras.

IMPLEMENTATION:

QUESTION 1: Add more Dense layers to the existing code and check how the accuracy changes.

• Install and import all the necessary libraries.

• Read the given CSV file which we have to work on and then split the data given to train and test.

• Add more dense layers to the existing layers.

  

• Addition of more dense layers increases accuracy and decreases loss.

QUESTION 2: Change the data source to Breast Cancer dataset and calculate the accuracy and loss.

• Read the given breast cancer dataset and infer the target column.

• Split the data to train and test.

• Use label encoder to convert the target column to numeric values.

• Calculate score using the hidden and output layers.

  

QUESTION 3: Normalize the data before feeding the data to the model and check how the normalization change your accuracy.

• Use the same dataset and follow the same procedure as in the question 2.

• Scale the data using standard scalar object and then send it to the train and test.

• Now calculate the score.