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코세라의 deeplearning.AI tensorflow developer 전문가 자격증 과정내에 Sequences, Time Series and Prediction
과정의 1주차 Sequences and Prediction 챕터의 코드 예제입니다.
time serise data를 traing data 포멧에 맞게 변환하는 과정을 각 print()마다 볼 수 있도록 되어있다.
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import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
print(tf.__version__)
dataset = tf.data.Dataset.range(10)
for val in dataset:
print(val.numpy())
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1)
for window_dataset in dataset:
for val in window_dataset:
print(val.numpy(), end=" ")
print()
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1, drop_remainder=True)
for window_dataset in dataset:
for val in window_dataset:
print(val.numpy(), end=" ")
print()
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1, drop_remainder=True)
dataset = dataset.flat_map(lambda window: window.batch(5))
for window in dataset:
print(window.numpy())
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1, drop_remainder=True)
dataset = dataset.flat_map(lambda window: window.batch(5))
dataset = dataset.map(lambda window: (window[:-1], window[-1:]))
for x,y in dataset:
print(x.numpy(), y.numpy())
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1, drop_remainder=True)
dataset = dataset.flat_map(lambda window: window.batch(5))
dataset = dataset.map(lambda window: (window[:-1], window[-1:]))
dataset = dataset.shuffle(buffer_size=10)
for x,y in dataset:
print(x.numpy(), y.numpy())
dataset = tf.data.Dataset.range(10)
dataset = dataset.window(5, shift=1, drop_remainder=True)
dataset = dataset.flat_map(lambda window: window.batch(5))
dataset = dataset.map(lambda window: (window[:-1], window[-1:]))
dataset = dataset.shuffle(buffer_size=10)
dataset = dataset.batch(2).prefetch(1)
for x,y in dataset:
print("x = ", x.numpy())
print("y = ", y.numpy())
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