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Flashcard 7628981144844

Tags
#deep-learning #keras #lstm #python #sequence
Question
the 4 different types of sequence prediction problems: 1. Sequence Prediction. 2. Sequence Classification. 3. Sequence [...]. 4. Sequence-to-Sequence Prediction
Answer
Generation

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the 4 different types of sequence prediction problems: 1. Sequence Prediction. 2. Sequence Classification. 3. Sequence Generation. 4. Sequence-to-Sequence Prediction

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Flashcard 7629342117132

Tags
#causality #statistics
Question
Exchangeability means that the treatment groups are exchangeable in the sense that if they were [...], the new treatment group would observe the same outcomes as the old treatment group
Answer
swapped

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Exchangeability means that the treatment groups are exchangeable in the sense that if they were swapped, the new treatment group would observe the same outcomes as the old treatment group

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Flashcard 7629351816460

Tags
#bayes #programming #r #statistics
Question
One way to summarize the uncertainty is by marking the [...] that are most credible and cover 95% of the distribution. This is called the highest density inter val (HDI)
Answer
span of values

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One way to summarize the uncertainty is by marking the span of values that are most credible and cover 95% of the distribution. This is called the highest density inter val (HDI) and is marked by the black bar on the floor of the distribution in Figure 2.

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Flashcard 7629356010764

Tags
#causality #statistics
Question
To identify a causal effect is to reduce a causal expression to a purely statistical expression. In this chapter, that means to reduce an expression from one that uses [...] notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and conditioning. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌)
Answer
potential outcome

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To identify a causal effect is to reduce a causal expression to a purely statistical expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and conditioning. This means that we can calculate the causal effect from just the observational di

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Flashcard 7629643058444

Tags
#abm #agent-based #machine-learning #model #priority
Question
Neural networks can also be used for nonlinear adaptive control in [...] systems
Answer
multi-agent

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Neural networks can also be used for nonlinear adaptive control in multi-agent systems

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Flashcard 7673663851788

Question

How do you check the login tokens for all running jupyter notebook instances?

[...] notebook list

Answer
jupyter

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How do you check the login tokens for all running jupyter notebook instances? jupyter notebook list






Annotation 7673665948940

#ML-engineering #ML_in_Action #learning #machine #software-engineering
ML engineers need just enough visualization skills to create plots and charts that communicate clearly what their research and models are doing, but not to develop dynamic web apps that have complex user experience (UX) components
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kering. They need just enough data engineering skills to build (and schedule the ETL for) feature datasets for their models, but not to construct a petabyte-scale streaming ingestion framework. <span>They need just enough visualization skills to create plots and charts that communicate clearly what their research and models are doing, but not to develop dynamic web apps that have complex user experience (UX) components. They also need just enough project management experience to know how to properly define, scope, and control a project to solve a problem, but they need not go through a Project Managem

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Flashcard 7673668832524

Tags
#English #vocabulary
Question

[...]

verb

  1. deliberately avoid using; abstain from.

    "he appealed to the crowd to ... violence"

Answer
eschew

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eschew /ɪsˈtʃuː,ɛsˈtʃuː/ Learn to pronounce verb gerund or present participle: eschewing deliberately avoid using; abstain from. "he appealed to the crowd to eschew violence"