Building Machine Learning Projects with TensorFlow by Rodolfo Bonnin

Author:Rodolfo Bonnin
Language: eng
Format: mobi, pdf
Publisher: Packt Publishing
Published: 2016-11-23T23:00:00+00:00

Alcohol

Malic acid

Ash

Alcalinity of ash

Magnesium

Total phenols

Flavanoids

Nonflavanoid phenols

Proanthocyanins

Color intensity

Hue

OD280/OD315 of diluted wines

Proline

To read the dataset, we will simply use the provided CSV file and pandas:

df = pd.read_csv("./wine.csv", header=0)

Dataset preprocessing

As the values on the csv begin at 1, we will normalize the values resting the bias:

y = df['Wine'].values-1

For the results, we will have to represent the options as a one hot list of arrays:

Y = tf.one_hot(indices = y, depth=3, on_value = 1., off_value = 0., axis = 1 , name = "a").eval()

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