Hfrxdjt

Im working on my first NN following a tensorflow tut and trying to use my own data.
After about 80 attempts of formatting my data and trying to load it into a dataset to train im throwing in the towel.

Here is how my data currently looks

syslog_data = [
[302014,0,0,63878,30,3,1], [302014,0,0,3891,0,0,0], [302014,0,0,15928,0,0,2], [305013,5,0,123,99999,0,3],
[302014,0,0,5185,0,0,0], [305013,5,0,123,99999,0,3], [302014,0,0,56085,0,0,0], [110002,4,2,50074,99999,0,4],

In this the last item in each list is the label.
If you can tell me if I need to reformat my data and how or just how to get it loaded into a dataset properly.

Thanks for any help or advice you can give

Here is the full code:

import tensorflow as tf
import numpy as np
from tensorflow.keras import layers
from . import syslog

print(tf.VERSION)
print(tf.keras.__version__)

model = tf.keras.Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(layers.Dense(64, activation='relu'))
# Add another:
model.add(layers.Dense(64, activation='relu'))
# Add a softmax layer with 10 output units:
model.add(layers.Dense(10, activation='softmax'))

model.compile(optimizer=tf.train.AdamOptimizer(0.001),
 loss='categorical_crossentropy',
 metrics=['accuracy'])

dataset = tf.data.dataset.from_tensor_slices(syslog)

model.fit(dataset, epochs=10, steps_per_epoch=30)