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08 Sep 2023 | The ML Dojo | Daily update
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| layout: post | ||
| title: Daily update | 08 September, 2023 | ||
| date: 2023-09-08 | ||
| --- | ||
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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/MachineLearning/comments/16ce68p/d_the_900000_deep_learning_salary?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/16cphta/this_is_how_a_recruiter_responded_after_i?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/16cnpvq/accepted_data_eng_offer_seems_more_like_bi?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/16cagf7/worthwhile_managed_el_extractload_tools_in_2023?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/datascience/comments/16cfkjw/should_i_change_teams_if_everyone_in_my_team_is?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> | ||
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| box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2); | ||
| transition: 0.3s; | ||
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| background-color: #F3F4F4; | ||
| } | ||
| p{ | ||
| margin-left: 3em; | ||
| padding-top: 1em; | ||
| } | ||
| .part2{ | ||
| display: grid; | ||
| grid-template-columns: 1fr 3fr; | ||
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| # StackExchange | ||
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| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625903/how-to-compare-fitted-survival-model-with-covariates-vs-kaplan-meier'>How to compare fitted survival model with covariates vs. Kaplan-Meier?</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> 89<br><b>Score:</b> 3<br><b>Tags:</b> <span class="badge badge-dark">survival</span> <span class="badge badge-dark">model-comparison</span> <span class="badge badge-dark">population</span> <span class="badge badge-dark">kaplan-meier</span> <span class="badge badge-dark">model-checking</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625928/understanding-the-results-of-the-glm-in-r'>Understanding the results of the GLM in R</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> 20<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">r</span> <span class="badge badge-dark">multiple-regression</span> <span class="badge badge-dark">generalized-linear-model</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625932/how-to-show-mathematically-that-random-effects-are-more-efficient-than-fixed-eff'>How to show mathematically that random effects are more efficient than fixed effects?</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> 36<br><b>Score:</b> 2<br><b>Tags:</b> <span class="badge badge-dark">mixed-model</span> <span class="badge badge-dark">econometrics</span> <span class="badge badge-dark">fixed-effects-model</span> <span class="badge badge-dark">efficiency</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://stats.stackexchange.com/questions/625947/in-case-of-no-correlation-can-a-model-make-predictions-above-the-expected-value'>In case of no correlation, can a model make predictions above the expected values?</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">classification</span> <span class="badge badge-dark">svm</span> <span class="badge badge-dark">convergence</span></p> | ||
| </div> | ||
| </div> | ||
| <br> | ||
| <div class="card"> | ||
| <h4><a href='https://cs.stackexchange.com/questions/161927/number-of-non-zero-elements-in-intersection-of-two-bloom-filters'>Number of non-zero elements in intersection of two bloom filters</a></h4> | ||
| <div class="part2"> | ||
| <img src="https://cdn.sstatic.net/Sites/cs/Img/[email protected]?v=324a3e0c2b03" alt="Img missing!" style="width:40%"> | ||
| <p><b>Source:</b> cs<br><b>Views:</b> 10<br><b>Score:</b> 1<br><b>Tags:</b> <span class="badge badge-dark">probability-theory</span> <span class="badge badge-dark">probabilistic-algorithms</span> <span class="badge badge-dark">bloom-filters</span></p> | ||
| </div> | ||
| </div> | ||
| # The End |