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on 24-Nov-2025 (Mon)

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Flashcard 7765911276812

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

What can visualize?

  • the data
  • model itself
  • the [...] of a model
  • predictions
Answer
training

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What can visualize? the data model itself the training of a model predictions

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TfC 01 regression
larger model Evaluating models Typical workflow: build a model -> fit it -> evaulate -> tweak -> fit > evaluate -> .... Building model: experiment Evaluation model: visualize <span>What can visualize? the data model itself the training of a model predictions ## 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_predict






Flashcard 7766198324492

Tags
#ML_in_Action #learning #machine #software-engineering
Question
ML engineering applies a system around this staggering level of complexity. It uses a set of standards, tools, [...], and methodology that aims to minimize the chances of abandoned, misguided, or irrelevant work being done in an effort to solve a business problem or need.
Answer
processes

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ML engineering applies a system around this staggering level of complexity. It uses a set of standards, tools, processes, and methodology that aims to minimize the chances of abandoned, misguided, or irrelevant work being done in an effort to solve a business problem or need.

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Flashcard 7766923414796

Question
lifelong deep neural networks ([...]),
Answer
L-DNN

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lifelong deep neural networks (L-DNN),

Original toplevel document

Deep Learning Has Reinvented Quality Control in Manufacturing—but It Hasn’t Gone Far Enough AI systems that make use of “lifelong learning” techniques are more flexible and faster to train
These so-called continual or lifelong learning systems, and in particular lifelong deep neural networks (L-DNN), were inspired by brain neurophysiology. These deep learning algorithms separate feature training and rule training and are able to add new rule information on the fly. While they still






Flashcard 7771817118988

Tags
#deep-learning #keras #lstm #python #sequence
Question
A time window based MLP outperformed the LSTM pure-[[...]] approach on certain time series prediction benchmarks solvable by looking at a few recent inputs only.
Answer
autoregression

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A time window based MLP outperformed the LSTM pure-[autoregression] approach on certain time series prediction benchmarks solvable by looking at a few recent inputs only.

Original toplevel document (pdf)

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