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Annotation 7553399524620

#data-science #infrastructure
The goal of the stack, which is introduced in the next section, is to unlock the four Vs: it should enable a greater volume and variety of projects, delivered with a higher velocity, without compromising validity of results. However, the stack doesn’t deliver projects by itself—successful projects are delivered by data scientists whose productivity is hopefully greatly improved by the stack
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Annotation 7762837114124

#abm #agent-based #machine-learning #model #priority #synergistic-integration
As demonstrated by Torrens et al. [9], the individual behavior in an agent-based model can be machine-learned from samples collected at the individual-agent level. In addition, modern ABM techniques can help in analysis through their ability to have adaptive agents in different changing environments [10]. The machine- learning-based inference model can thus provide an alternative to coarse models of agents and can extend traditional agent-based transition schemes that hardcode agents’ behavior rules into a model—apriori
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es for behaviors at the scale of individual agents. This gives them little choice but to employ abstract proxy representation of agent behavior, which is not suitable for quantitative analysis. <span>As demonstrated by Torrens et al. [9], the individual behavior in an agent-based model can be machine-learned from samples collected at the individual-agent level. In addition, modern ABM techniques can help in analysis through their ability to have adaptive agents in different changing environments [10]. The machine- learning-based inference model can thus provide an alterna- tive to coarse models of agents and can extend traditional agent-based transition schemes that hardcode agents’ behavior rules into a model—apriori[9]. Accordingly, integrating ABM and ML in decision-making can combine the inductive and deductive reasoning approaches, enabling us to describe the way that decisions can be made or im

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Flashcard 7789327551756

Tags
#pytest #python #unittest
Question
Beware of [...] return values!
0.1 + 0.1 + 0.1 == 0.3 Sometimes false
Answer
float

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Beware of float return values! 0.1 + 0.1 + 0.1 == 0.3 Sometimes false

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Beware of float return values! 0.1 + 0.1 + 0.1 == 0.3 Sometimes false assert 0.1 + 0.1 + 0.1 == 0.3, "Usual way to compare does not always work with floats!" Instead use: assert 0.1 + 0.1 + 0.1 == pytest.approx(0.3)






Annotation 7794594286860

#deep-learning #keras #lstm #python #sequence
Alternately, for classification problems, we can use the predict classes() function that will automatically convert uncrisp predictions to crisp integer class values.
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may be in the form of an array of probabilities (assuming a one hot encoded output variable) that may need to be converted to a single class output prediction using the argmax() NumPy function. <span>Alternately, for classification problems, we can use the predict classes() function that will automatically convert uncrisp predictions to crisp integer class values. <span>

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Annotation 7794595859724

#deep-learning #keras #lstm #python #sequence
The predictions will be returned in the format provided by the output layer of the network. In the case of a regression problem, these predictions may be in the format of the problem directly, provided by a linear activation function.
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The predictions will be returned in the format provided by the output layer of the network. In the case of a regression problem, these predictions may be in the format of the problem directly, provided by a linear activation function. For a binary classification problem, the predictions may be an array of probabilities for the first class that can be converted to a 1 or 0 by rounding. For a multiclass classification

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Annotation 7794597432588

#git #software-engineering

lepiej mieć więcej mniejszych, logicznie powiązanych commitów.

W świecie inżynierii oprogramowania to podejście nazywa się Atomic Commits
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Zdecydowana większość doświadczonych programistów i zespołów zgodzi się co do jednej odpowiedzi: lepiej mieć więcej mniejszych, logicznie powiązanych commitów. W świecie inżynierii oprogramowania to podejście nazywa się Atomic Commits (Commity Atomowe).

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Commity w git
Zdecydowana większość doświadczonych programistów i zespołów zgodzi się co do jednej odpowiedzi: lepiej mieć więcej mniejszych, logicznie powiązanych commitów. W świecie inżynierii oprogramowania to podejście nazywa się Atomic Commits (Commity Atomowe). Oto szczegółowe wyjaśnienie, dlaczego to podejście jest lepsze i jak je stosować w praktyce. 1. Złota zasada: Atomic Commits Commit powinien być "atomowy", co oznacza, że jest to najmni



Annotation 7794599005452

#git #software-engineering
Zdecydowana większość doświadczonych programistów i zespołów zgodzi się co do jednej odpowiedzi: lepiej mieć więcej mniejszych, logicznie powiązanych commitów.
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Zdecydowana większość doświadczonych programistów i zespołów zgodzi się co do jednej odpowiedzi: lepiej mieć więcej mniejszych, logicznie powiązanych commitów. W świecie inżynierii oprogramowania to podejście nazywa się Atomic Commits (Commity Atomowe).

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Commity w git
Zdecydowana większość doświadczonych programistów i zespołów zgodzi się co do jednej odpowiedzi: lepiej mieć więcej mniejszych, logicznie powiązanych commitów. W świecie inżynierii oprogramowania to podejście nazywa się Atomic Commits (Commity Atomowe). Oto szczegółowe wyjaśnienie, dlaczego to podejście jest lepsze i jak je stosować w praktyce. 1. Złota zasada: Atomic Commits Commit powinien być "atomowy", co oznacza, że jest to najmni



Flashcard 7794602937612

Tags
#knative #okd #serverless
Question

Scaling based on concurrency

command: kn [...] update qura-rest-api --concurrency-limit 1 --scale-window=10s

Answer
service

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Skalowanie w Knative serving
Scaling based on concurrency command: kn service update qura-rest-api --concurrency-limit 1 --scale-window=10s






Flashcard 7794605034764

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, processes, and [...] 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
methodology

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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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