Hacker News<p>Time Series Forecasting with Graph Transformers</p><p><a href="https://kumo.ai/research/time-series-forecasting/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">kumo.ai/research/time-series-f</span><span class="invisible">orecasting/</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/TimeSeriesForecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeriesForecasting</span></a> <a href="https://mastodon.social/tags/GraphTransformers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GraphTransformers</span></a> <a href="https://mastodon.social/tags/AIResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIResearch</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a></p>
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#timeseriesforecasting
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MongoDBDemand Forecasting With MongoDB Time Series and Edge-Server Written by: Nitish Joshi (Solutions A...<br><br><a href="https://medium.com/mongodb/demand-forecasting-with-mongodb-time-series-and-edge-server-198aa5a5511e?source=rss----380d02a087f---4" rel="nofollow noopener" target="_blank">https://medium.com/mongodb/demand-forecasting-with-mongodb-time-series-and-edge-server-198aa5a5511e?source=rss----380d02a087f---4</a><br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/time-series-forecasting" target="_blank">#time-series-forecasting</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/edge-computing" target="_blank">#edge-computing</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/mongodb" target="_blank">#mongodb</a><br><br><a href="https://awakari.com/pub-msg.html?id=GxjVaoGhVxkEcz2pCYqeHlzgCKO&interestId=MongoDB" rel="nofollow noopener" target="_blank">Result Details</a>
Data Blogger<p>Why (and how) you should create a baseline model before you train your final model <a href="https://mastodon.social/tags/TimeSeriesForecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeriesForecasting</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/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> 📈📚 <a href="https://towardsdatascience.com/baseline-models-in-time-series-c76d44a826b3" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">towardsdatascience.com/baselin</span><span class="invisible">e-models-in-time-series-c76d44a826b3</span></a></p>
Alex Zap<p><a href="https://mastodon.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://mastodon.social/tags/TimeSeriesForecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeriesForecasting</span></a><br><a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</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/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PredictiveAnalytics</span></a><br>We compare performance of TSA models: the 3 best performing models are Prophet, SARIMAX, and Holt-Winters.<br><a href="https://mastodon.social/tags/Sales" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Sales</span></a> <a href="https://mastodon.social/tags/SalesStrategy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SalesStrategy</span></a> <a href="https://mastodon.social/tags/SalesTips" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SalesTips</span></a> <a href="https://mastodon.social/tags/SalesProductivity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SalesProductivity</span></a></p><p><a href="http://newdigitals.org/2023/12/12/evaluation-of-ml-sales-forecasting-tslearn-random-walk-holt-winters-sarimax-garch-prophet-and-lstm/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="ellipsis">newdigitals.org/2023/12/12/eva</span><span class="invisible">luation-of-ml-sales-forecasting-tslearn-random-walk-holt-winters-sarimax-garch-prophet-and-lstm/</span></a></p>
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