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#ML-engineering #ML_in_Action #learning #machine #software-engineering

Data scientists are also expected to be familiar with additional realms of competency. From

- mid-level DE skills (you have to get your data for your data science from somewhere, right?),
- software development skills,
- project management skills,
- visualization skills,
- presentation skills

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Data scientists are also expected to be familiar with additional realms of competency. From mid-level DE skills (you have to get your data for your data science from somewhere, right?), software development skills, project management skills, visualization skills, and presentation skills, the list grows ever longer, and the volumes of experience that need to be gained become rather daunting. It’s not much of a surprise, considering all of this, that “just figuring it ou

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Flashcard 7788719115532

Tags
#causal #inference
Question
Inverse probability [...] is not technically a G-method. While it shares the fundamental goal of addressing confounding and selection bias, it employs a different mathematical framework and estimation approach
Answer
matching

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Inverse probability matching (propensity score matching) is not technically a G-method. While it shares the fundamental goal of addressing confounding and selection bias, it employs a different mathematical framewo

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The G-methods family, as developed by James Robins and colleagues, specifically includes: Inverse probability weighting (IPW) G-computation G-estimation of structural nested models Inverse probability matching (propensity score matching) is not technically a G-method. While it shares the fundamental goal of addressing confounding and selection bias, it employs a different mathematical framework and estimation approach







Flashcard 7789532810508

Tags
#deep-learning #keras #lstm #python #sequence
Question
Truncated Backpropagation Through Time, or TBPTT, is a modified version of the [...] training algorithm
Answer
BPTT

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Truncated Backpropagation Through Time, or TBPTT, is a modified version of the BPTT training algorithm

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#recurrent-neural-networks #rnn
the proposed approach can leverage the complete transaction histories and deliver excellent long-term forecasts for individual customers. Such a perspective seems to be particularly useful for the rich stream of information accompanying customer-firm interactions in modern digital business environments (Wedel & Kannan, 2016; Dzyabura & Peres, 2021) where anything including high-dimensional data can become available as a covariate
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s the inability to make projections into the distant future, but despite the ‘‘one time step ahead” property of its predictions we show, by means of a calibration length sensitivity study, that <span>the proposed approach can leverage the complete transaction histories and deliver excellent long-term forecasts for individual customers. Such a perspective seems to be particularly useful for the rich stream of information accompanying customer-firm interactions in modern digital business environments (Wedel & Kannan, 2016; Dzyabura & Peres, 2021) where anything including high-dimensional data can become available as a covariate <span>

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If an argument, action, or situation is untenable, it cannot be supported or defended from criticism.
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untenable adjective formal uk /ʌnˈtenəbl/ us If an argument, action, or situation is untenable, it cannot be supported or defended from criticism.

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untenable adjective formal uk /ʌnˈtenəbl/ us If an argument, action, or situation is untenable, it cannot be supported or defended from criticism. nie do obrony lub utrzymania an untenable position Examples: Following the scandal, the minister resigned saying that his position had become untenable The government’s actions are unte





#causality #has-images #statistics
Minimality would tell us to factorize 𝑃(𝑥, 𝑦) as 𝑃(𝑥)𝑃(𝑦|𝑥) , and it would tell us that no additional independencies (𝑋 ⊥⊥ 𝑌) exist in 𝑃 that are minimal with respect to Figure 3.8.
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so allow us to factorize 𝑃(𝑥, 𝑦) as 𝑃(𝑥)𝑃(𝑦) , meaning it allows distributions where 𝑋 and 𝑌 are independent. In contrast, the minimality assumption does not allow this additional independence. <span>Minimality would tell us to factorize 𝑃(𝑥, 𝑦) as 𝑃(𝑥)𝑃(𝑦|𝑥) , and it would tell us that no additional independencies (𝑋 ⊥⊥ 𝑌) exist in 𝑃 that are minimal with respect to Figure 3.8. <span>

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#feature-engineering #lstm #recurrent-neural-networks #rnn
To increase the match of the model's effective capacity and the complexity of the task at hand, the analyst needs to tune both the parameters and the hyperparameters of the model.
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ity of a model might be lower than its representational capacity because of limitations and shortcomings, such as imperfect optimization or suboptimal hyperparameters (Goodfellow et al., 2016). <span>To increase the match of the model's effective capacity and the complexity of the task at hand, the analyst needs to tune both the parameters and the hyperparameters of the model. <span>

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