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on 24-Oct-2025 (Fri)

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Flashcard 7765207944460

Tags
#has-images #tensorflow #tensorflow-certificate
[unknown IMAGE 7626420784396]
Question

## The 3 sets (or actually 2 sets: training and test set) - USING ONLY TensorFlow

tf.random.set_seed(999)

X_train, X_test = tf.split(tf.random.shuffle(X, seed=42), [...]=[40, 10])

Answer
num_or_size_splits

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## The 3 sets (or actually 2 sets: training and test set) - USING ONLY TensorFlow tf.random.set_seed(999) X_train, X_test = tf.split(tf.random.shuffle(X, seed=42), num_or_size_splits=[40, 10])

Original toplevel document

TfC 01 regression
> evaulate -> tweak -> fit > evaluate -> .... Building model: experiment Evaluation model: visualize What can visualize? the data model itself the training of a model predictions <span>## The 3 sets (or actually 2 sets: training and test set) tf.random.set_seed(999) X_train, X_test = tf.split(tf.random.shuffle(X, seed=42), num_or_size_splits=[40, 10]) def plot_predictions(train_data = X_train, train_labels = y_train, test_data = X_test, test_labels = y_test, predictions = y_pred): """ Plots training data, testing_data """ plt.figure(






Flashcard 7765209779468

Tags
#deep-learning #keras #lstm #python #sequence
Question
LSTM’s special strength, namely, to learn to remember single events for very long, [...] time periods
Answer
unknown

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scheduled repetition interval               last repetition or drill

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LSTM’s special strength, namely, to learn to remember single events for very long, unknown time periods

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Flashcard 7765211614476

Tags
#causality #statistics
Question
Given that we have tools to measure association, how can we isolate causation? In other words, how can we ensure that the association we measure is causation, say, for measuring the causal effect of 𝑋 on π‘Œ ? Well, we can do that by ensuring that there is no non-causal [...] flowing between 𝑋 and π‘Œ
Answer
association

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on? In other words, how can we ensure that the association we measure is causation, say, for measuring the causal effect of 𝑋 on π‘Œ ? Well, we can do that by ensuring that there is no non-causal <span>association flowing between 𝑋 and π‘Œ <span>

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Flashcard 7765215284492

Tags
#causality #statistics
Question
Whenever, do(𝑑) appears after the conditioning bar, it means that everything in that expression is in the post-intervention world where the intervention do(𝑑) occurs. For example, 𝔼[π‘Œ | do(𝑑), 𝑍 = 𝑧] refers to the expected outcome in the subpopulation where 𝑍 = 𝑧 after the whole [...] has taken treatment 𝑑 .
Answer
subpopulation

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xpression is in the post-intervention world where the intervention do(𝑑) occurs. For example, 𝔼[π‘Œ | do(𝑑), 𝑍 = 𝑧] refers to the expected outcome in the subpopulation where 𝑍 = 𝑧 after the whole <span>subpopulation has taken treatment 𝑑 . <span>

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