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Annotation 7103825710348

We can summarize the 3 key benefits of LSTMs as:
#deep-learning #keras #lstm #python #sequence

We can summarize the 3 key benefits of LSTMs as:

1. Overcomes the technical problems of training an RNN, namely vanishing and exploding gradients.

2. Possesses memory to overcome the issues of long-term temporal dependency with input sequences

3. Process input sequences and output sequences time step by time step, allowing variable length inputs and outputs
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Annotation 7103946558732

#feature-engineering #lstm #recurrent-neural-networks #rnn
Finally, the field of deep learning in general, and recurrent neural networks, in particular, is evolving rapidly. Many alternative model specifications and network architectures offer the promises of improvements over vanilla LSTM models. They have already been proven superior in some domains. Such alternative specifications include Gated Recurrent Units, BiLSTM (Siami-Namini, Tavakoli, & Namin, 2019), Multi-Dimensional LSTM (Graves & Schmidhuber, 2009), Neural Turing Machines (Graves, Wayne, & Danihelka, 2014), Attention-Based RNN and its various implementations (e.g., Bahdanau, Cho, & Bengio, 2014; Luong, Pham, & Manning, 2015), or Transformers (Vaswani et al., 2017). It is not clear that one architecture will lead systematically to the best possible performance. Lacking benchmarking studies, the analyst may be required to experiment with several models (although, as demonstrated in this paper, a simple LSTM model already provides excellent performance)
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Annotation 7559036931340

Using ls and cd comands on network folders
#filesharing #linux #network

Using ls and cd comands on network folders

This depends on how is the NAS setup.

Does it use windows sharing? Then you can use smbclient to connect to the server and there you can use lsand cd.
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Flashcard 7560218414348

Question
investigation, ruling that the Israeli government was not responsible for Corrie's death.[5] The ruling was met with criticism by human rights organizations such as Amnesty International and Human Rights Watch, and by
Answer
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Rachel Corrie - Wikipedia
soldiers had acted with reckless neglect.[5] They sued for a symbolic one U.S. dollar in damages. An Israeli court rejected their suit in August 2012 and upheld the results of the 2003 military <span>investigation, ruling that the Israeli government was not responsible for Corrie's death.[5] The ruling was met with criticism by human rights organizations such as Amnesty International and Human Rights Watch, and by activists.[14][15][16] An appeal against this ruling was heard on May 21, 2014. On February 14, 2015, the Supreme Court of Israel rejected the appeal.[18] Early life Corrie was born on






Annotation 7560227851532

#recurrent-neural-networks #rnn

More precisely, firms following a customer-centric business approach need to know how their clientele will behave on different future time scales and levels of behavioral complexity (Gupta & Lehmann, 2005; Fader, 2020):

- What are they going to do in the immediate future and when do they make their next transaction with the focal company, if any?

- Are some of them at risk of stopping doing business with the firm?

- How exactly do seasonality and other time-based events influence the propensity of customers to buy?
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Anticipating future customer behavior and making individual-level predictions for a firm’s customer base is crucial to any organization that wants to manage its customer portfolio proactively. <span>More precisely, firms following a customer-centric business approach need to know how their clientele will behave on different future time scales and levels of behavioral complexity (Gupta & Lehmann, 2005; Fader, 2020): What are they going to do in the immediate future and when do they make their next transaction with the focal company, if any? Are some of them at risk of stopping doing business with the firm? How exactly do seasonality and other time-based events influence the propensity of customers to buy? <span>

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Annotation 7560229424396

#recurrent-neural-networks #rnn
Anticipating future customer behavior and making individual-level predictions for a firm’s customer base is crucial to any organization that wants to manage its customer portfolio proactively.
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Anticipating future customer behavior and making individual-level predictions for a firm’s customer base is crucial to any organization that wants to manage its customer portfolio proactively. More precisely, firms following a customer-centric business approach need to know how their clientele will behave on different future time scales and levels of behavioral complexity (Gu

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Annotation 7560230997260

#recurrent-neural-networks #rnn
Contrary to subscription-based or contractual settings where customer ‘‘churn” events are directly observable, customer defection in non-contractual business settings is by definition unobserved by the firm and thus needs to be indirectly inferred from past transaction behavior (Reinartz & Kumar, 2000; Gupta et al., 2006).
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e to derive such individual-level predictions is particularly demanding in the context of non-contractual settings (such as most retail businesses, online media consumption, charity donations). <span>Contrary to subscription-based or contractual settings where customer ‘‘churn” events are directly observable, customer defection in non-contractual business settings is by definition unobserved by the firm and thus needs to be indirectly inferred from past transaction behavior (Reinartz & Kumar, 2000; Gupta et al., 2006). The specific challenge in such settings is to accurately and timely inform managers on the subtle distinction between a pending defection event (i.e., a customer stops doing business wi

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Flashcard 7560233880844

Tags
#R #ggplot2
Question

Marginal distributions can now be made in R using [...], a new ggplot2 extension. You can make linear regression with marginal distributions using histograms, densities, box plots, and more. Bonus - The side panels are super customizable for uncovering complex relationships.

Here are two examples of what you will do in this tutorial!

Answer
ggside

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Side-Plot Tutorial with ggside
Marginal distributions can now be made in R using ggside, a new ggplot2 extension. You can make linear regression with marginal distributions using histograms, densities, box plots, and more. Bonus - The side panels are super customizable for






Flashcard 7560237288716

Tags
#deep-learning #keras #lstm #python #sequence
Question

We can summarize the 3 key benefits of LSTMs as:

1. Overcomes the [...] problems of training an RNN, namely vanishing and exploding gradients.

2. Possesses memory to overcome the issues of long-term temporal dependency with input sequences

3. Process input sequences and output sequences time step by time step, allowing variable length inputs and outputs

Answer
technical

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scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

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We can summarize the 3 key benefits of LSTMs as: 1. Overcomes the technical problems of training an RNN, namely vanishing and exploding gradients. 2. Possesses memory to overcome the issues of long-term temporal dependency with input sequences 3. Process input

Original toplevel document (pdf)

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Flashcard 7560239910156

Tags
#filesharing #linux #network
Question

Using ls and cd comands on network folders

This depends on how is the NAS setup.

Does it use windows sharing? Then you can use [...] to connect to the server and there you can use lsand cd.

Answer
smbclient

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Using ls and cd comands on network folders
Using ls and cd comands on network folders This depends on how is the NAS setup. Does it use windows sharing? Then you can use smbclient to connect to the server and there you can use lsand cd.






Annotation 7560241745164

#R #debugger #shiny
Unlike breakpoints, browser() works everywhere, so it’s suitable for use in any code invoked by your Shiny app.
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Debuging shiny applications
The browser() statement is another useful debugging tool. It acts like a breakpoint–when evaluated, it halts execution and enters the debugger. You can add it anywhere an R expression is valid. <span>Unlike breakpoints, browser() works everywhere, so it’s suitable for use in any code invoked by your Shiny app. You can also invoke browser() conditionally to create conditional breakpoints; for instance: if (input$bins > 50) browser() The downside of browser() is that you need to re-run your