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48 Beiträge44 Beteiligte8 Beiträge heute
Jürgen<p>What a surprise.</p><p><a href="https://mastodon.nl/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.nl/tags/tech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tech</span></a> <a href="https://mastodon.nl/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technology</span></a> <a href="https://mastodon.nl/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mastodon.nl/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> <a href="https://mastodon.nl/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>programming</span></a> <a href="https://mastodon.nl/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://mastodon.nl/tags/genAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>genAI</span></a> <a href="https://mastodon.nl/tags/generativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>generativeAI</span></a> <a href="https://mastodon.nl/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://mastodon.nl/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a> <a href="https://mastodon.nl/tags/llms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llms</span></a></p><p><a href="https://www.techradar.com/pro/almost-all-genai-pilots-companies-deploy-are-failing-are-they-really-worth-the-hype" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">techradar.com/pro/almost-all-g</span><span class="invisible">enai-pilots-companies-deploy-are-failing-are-they-really-worth-the-hype</span></a></p>
Posit<p>Positron's Layout lets you build your ideal workspace. 🛠️</p><p>You have access to all your tools, from the Editor to the Console, the Plots Viewer to the Connections Pane, and more.</p><p>Learn more: <a href="https://positron.posit.co/layout.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">positron.posit.co/layout.html</span><span class="invisible"></span></a><br><a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://fosstodon.org/tags/Positron" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Positron</span></a> <a href="https://fosstodon.org/tags/IDE" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>IDE</span></a></p>
Du coq à l’asne<p>En train de tester le code d'une petite application <a href="https://social.sciences.re/tags/Shiny" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Shiny</span></a>-R pour visualiser une partie de mes données <a href="https://social.sciences.re/tags/TEI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TEI</span></a> <br><a href="https://social.sciences.re/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://social.sciences.re/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a> <a href="https://ducoqalane.hypotheses.org/2397" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">ducoqalane.hypotheses.org/2397</span><span class="invisible"></span></a></p>
Talk Python Podcast<p>Episode #516: Accelerating Python Data Science at NVIDIA with Ben Zaitlen and <span class="h-card" translate="no"><a href="https://fosstodon.org/@mkennedy" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>mkennedy</span></a></span> <a href="https://fosstodon.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a></p><p><a href="https://talkpython.fm/episodes/show/516/accelerating-python-data-science-at-nvidia" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">talkpython.fm/episodes/show/51</span><span class="invisible">6/accelerating-python-data-science-at-nvidia</span></a></p>
DSLC Videos<p>Recent <span class="h-card" translate="no"><a href="https://fosstodon.org/@DSLC" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>DSLC</span></a></span> club meetings:</p><p>:rstats: Advanced R: Names and values <a href="https://youtu.be/_GIEEMuZYrs" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/_GIEEMuZYrs</span><span class="invisible"></span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a></p><p>From the <span class="h-card" translate="no"><a href="https://fosstodon.org/@DSLC" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>DSLC</span></a></span> :rstats:​chives:</p><p>:rstats: Explanatory Model Analysis: Ceteris-paribus Profiles <a href="https://youtu.be/bSMWIVtrZ_4" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/bSMWIVtrZ_4</span><span class="invisible"></span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a></p><p>:rstats: rlang docs: Function arguments <a href="https://youtu.be/I0g3DS8K1-w" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/I0g3DS8K1-w</span><span class="invisible"></span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a></p><p>:rstats: Mastering Shiny: Graphics <a href="https://youtu.be/KwUE61NVDUk" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">youtu.be/KwUE61NVDUk</span><span class="invisible"></span></a> <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a></p><p>Visit <a href="https://dslc.video" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">dslc.video</span><span class="invisible"></span></a> for hours of new <a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> videos every week!</p>
Blosc Development Team<p>🚀 We are thrilled to announce *TreeStore*, a new class in Python-Blosc2! It lets you give your datasets a hierarchical structure while keeping the speed and efficiency of `NDArray` instances. ⚡️</p><p>📝 We've blogged all about it here:<br><a href="https://www.blosc.org/posts/new-treestore-blosc2/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">blosc.org/posts/new-treestore-</span><span class="invisible">blosc2/</span></a></p><p>It's in beta, and you can start using it now in the latest Python-Blosc2 v3.7.2. Enjoy!</p><p><a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://fosstodon.org/tags/Blosc2" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Blosc2</span></a> <a href="https://fosstodon.org/tags/TreeStore" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TreeStore</span></a> <a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
Hacker News<p>Why Semantic Layers Matter (and how to build one with DuckDB)</p><p><a href="https://motherduck.com/blog/semantic-layer-duckdb-tutorial/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">motherduck.com/blog/semantic-l</span><span class="invisible">ayer-duckdb-tutorial/</span></a></p><p><a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HackerNews</span></a> <a href="https://mastodon.social/tags/SemanticLayers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SemanticLayers</span></a> <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DuckDB</span></a> <a href="https://mastodon.social/tags/DataAnalytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataAnalytics</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/Tutorial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Tutorial</span></a></p>
Antwortete im Thread
Eric Maugendre

Logistic regression may be used for classification.

In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.

The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.

More: baeldung.com/cs/gradient-desce

#optimization#algebra#linearAlgebra
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