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07 Sep 2023 | The ML Dojo | Daily update
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| layout: post | ||
| title: Daily update | 07 September, 2023 | ||
| date: 2023-09-07 | ||
| --- | ||
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| <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> | ||
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| <script src='https://storage.ko-fi.com/cdn/scripts/overlay-widget.js'></script> | ||
| <script> | ||
| kofiWidgetOverlay.draw('themldojo', { | ||
| 'type': 'floating-chat', | ||
| 'floating-chat.donateButton.text': 'Support me', | ||
| 'floating-chat.donateButton.background-color': '#f45d22', | ||
| 'floating-chat.donateButton.text-color': '#fff' | ||
| }); | ||
| </script> | ||
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| <iframe id="reddit-embed" src="https://www.redditmedia.com/r/datascience/comments/16bs1bd/why_so_many_data_scientist_complain_about_their?ref_source=embed&ref=share&embed=true" sandbox="allow-scripts allow-same-origin allow-popups" style="border: none;" height="300" width="100%" scrolling="yes"></iframe> | ||
| <hr style="width:100%;text-align:left;margin-left:0"> | ||
| <iframe id="reddit-embed" src="https://www.redditmedia.com/r/MachineLearning/comments/16bbvjk/r_can_llms_learn_from_a_single_example?ref_source=embed&ref=share&embed=true" sandbox="allow-scripts allow-same-origin allow-popups" style="border: none;" height="300" width="100%" scrolling="yes"></iframe> | ||
| <hr style="width:100%;text-align:left;margin-left:0"> | ||
| <iframe id="reddit-embed" src="https://www.redditmedia.com/r/dataengineering/comments/16be6f8/data_engineering_projects_are_hard_to_showcase?ref_source=embed&ref=share&embed=true" sandbox="allow-scripts allow-same-origin allow-popups" style="border: none;" height="300" width="100%" scrolling="yes"></iframe> | ||
| <hr style="width:100%;text-align:left;margin-left:0"> | ||
| <iframe id="reddit-embed" src="https://www.redditmedia.com/r/MachineLearning/comments/16boda9/d_why_rlhf_instead_of_direct_ranking_loss?ref_source=embed&ref=share&embed=true" sandbox="allow-scripts allow-same-origin allow-popups" style="border: none;" height="300" width="100%" scrolling="yes"></iframe> | ||
| <hr style="width:100%;text-align:left;margin-left:0"> | ||
| <iframe id="reddit-embed" src="https://www.redditmedia.com/r/dataengineering/comments/16brzy2/i_built_an_aipowered_tool_that_can_turn_any?ref_source=embed&ref=share&embed=true" sandbox="allow-scripts allow-same-origin allow-popups" style="border: none;" height="300" width="100%" scrolling="yes"></iframe> | ||
| <hr style="width:100%;text-align:left;margin-left:0"> | ||
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| <style> | ||
| .card { | ||
| box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2); | ||
| transition: 0.3s; | ||
| width: 100%; | ||
| background-color: #F3F4F4; | ||
| } | ||
| p{ | ||
| margin-left: 3em; | ||
| padding-top: 1em; | ||
| } | ||
| .part2{ | ||
| display: grid; | ||
| grid-template-columns: 1fr 3fr; | ||
| } | ||
| h4{ | ||
| margin: 1em; | ||
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| # StackExchange | ||
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| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625851/distribution-of-min-j-ge-1x-1x-2-cdotsx-j-j-when-x-is-are-i-i-d-t'>Distribution of $\min_{j\ge 1}(X_1+X_2+\cdots+X_j)/j$ when $X_i$'s are i.i.d $\text{Exp}(1)$</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/stats/Img/[email protected]?v=344f57aa10cc" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> stats<br><b>Views:</b> 46<br><b>Score:</b> 3<br><b>Tags:</b> <span class="badge badge-dark">distributions</span> <span class="badge badge-dark">uniform-distribution</span> <span class="badge badge-dark">exponential-distribution</span> <span class="badge badge-dark">extreme-value</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625847/censored-regression-model'>Censored Regression model</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/stats/Img/[email protected]?v=344f57aa10cc" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> stats<br><b>Views:</b> 8<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">r</span> <span class="badge badge-dark">optimization</span> <span class="badge badge-dark">economics</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625821/nested-data-correction-with-mixed-models'>Nested data correction with mixed models</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/stats/Img/[email protected]?v=344f57aa10cc" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> stats<br><b>Views:</b> 22<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">mixed-model</span> <span class="badge badge-dark">anova</span> <span class="badge badge-dark">lme4-nlme</span> <span class="badge badge-dark">nested-data</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625838/how-to-calculate-significance-of-the-number-of-deponent-verbs-with-a-certain-fea'>How to calculate significance of the number of deponent verbs with a certain feature?</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/stats/Img/[email protected]?v=344f57aa10cc" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> stats<br><b>Views:</b> 29<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">hypothesis-testing</span> <span class="badge badge-dark">natural-language</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625845/why-use-a-scoring-rule-different-from-the-loss-function'>Why use a scoring rule different from the loss function?</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/stats/Img/[email protected]?v=344f57aa10cc" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> stats<br><b>Views:</b> 53<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">regression</span> <span class="badge badge-dark">maximum-likelihood</span> <span class="badge badge-dark">model-evaluation</span> <span class="badge badge-dark">scoring-rules</span></p> | ||
| </div> | ||
| </div> | ||
| # The End |