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R-Ladies Rome<p>🎥 Missed <span class="h-card" translate="no"><a href="https://mstdn.social/@ramikrispin" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>ramikrispin</span></a></span> <span class="h-card" translate="no"><a href="https://fosstodon.org/@rladiesrome" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>rladiesrome</span></a></span> on using linear regression for forecasting time series? No worries! Catch the beginner-friendly session on YouTube</p><p>Enhance your skills now read our blog post and watch the recording: 👉 <a href="https://rladiesrome.org/talks/2025/meetup/07032025_RamiKrispin.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">rladiesrome.org/talks/2025/mee</span><span class="invisible">tup/07032025_RamiKrispin.html</span></a> <br><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/Forecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Forecasting</span></a> <a href="https://fosstodon.org/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a></p>
R-Ladies Rome<p>📢 Don’t forget!<br>Join us today at 6PM CEST for our R-Ladies Rome workshop with @@ramikrispin:<br>“Forecasting Time Series with Linear Regression: A Feature-Driven Approach” 📈</p><p>🔗 <a href="https://www.meetup.com/rladies-rome/events/308574280" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">meetup.com/rladies-rome/events</span><span class="invisible">/308574280</span></a> </p><p><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/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</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/RLadiesRome" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RLadiesRome</span></a> <a href="https://fosstodon.org/tags/Rusers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Rusers</span></a> <a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
screwlisp<p><a href="https://gamerplus.org/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>programming</span></a> <a href="https://gamerplus.org/tags/graphing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>graphing</span></a> <a href="https://gamerplus.org/tags/plotting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>plotting</span></a> <a href="https://gamerplus.org/tags/visualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>visualization</span></a> <a href="https://gamerplus.org/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://gamerplus.org/tags/gnuplot" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gnuplot</span></a> <a href="https://gamerplus.org/tags/commonLisp" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>commonLisp</span></a> <a href="https://gamerplus.org/tags/lisp" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lisp</span></a> <a href="https://gamerplus.org/tags/example" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>example</span></a> <a href="https://screwlisp.small-web.org/programming/common-lisp-invoking-gnuplot/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">screwlisp.small-web.org/progra</span><span class="invisible">mming/common-lisp-invoking-gnuplot/</span></a><br>I could not even find my own previous articles and <a href="https://gamerplus.org/tags/demos" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>demos</span></a> of this online!</p><p>I used <a href="https://gamerplus.org/tags/uiop" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>uiop</span></a> run-program to handle one specific case like</p><p>(gnuplot "bad title" '((1 2) (3 4)) '((5 6) (7 8)))<br>or equivalently,<br>(apply 'gnuplot "bad title" '(((1 2) (3 4)) ((5 6) (7 8))))</p><p>Do you personally have an example? I remember it being hard to dredge up gnuplot examples but this is beyond silly.</p>
Steven P. Sanderson II, MPH<p>📊 Just released: RandomWalker 0.3.0! Now you can generate random walks in up to 3 dimensions. This is a must-read for R programmers looking to enhance their simulations.</p><p>Dive into the details: [<a href="https://www.spsanderson.com/steveondata/posts/2025-05-09/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">spsanderson.com/steveondata/po</span><span class="invisible">sts/2025-05-09/</span></a></p><p><a href="https://mstdn.social/tags/Data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Data</span></a> <a href="https://mstdn.social/tags/RLang" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RLang</span></a> <a href="https://mstdn.social/tags/Stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Stats</span></a> <a href="https://mstdn.social/tags/RData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RData</span></a> <a href="https://mstdn.social/tags/Blog" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Blog</span></a> <a href="https://mstdn.social/tags/CRAN" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CRAN</span></a> <a href="https://mstdn.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://mstdn.social/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a> <a href="https://mstdn.social/tags/RandomWalker" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RandomWalker</span></a></p>
PaquitoBernard<p>I am looking for a postdoc 'Environmental and behavioral health in a changing climate' (1/2)</p><p>2 years in <a href="https://masto.ai/tags/Rennes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Rennes</span></a> <a href="https://masto.ai/tags/france" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>france</span></a> <a href="https://masto.ai/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://masto.ai/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a> </p><p>We are looking for a postdoctoral researcher to help us understand the short-term impacts of environmental conditions on mental health, sleep and physical activity related behaviors. Future findings will help us better anticipate present and future consequences of climate change on bike use and sleep. </p><p><a href="https://masto.ai/tags/academia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>academia</span></a> <a href="https://masto.ai/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> <a href="https://masto.ai/tags/climatechange" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>climatechange</span></a> <a href="https://masto.ai/tags/health" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>health</span></a></p>
OpenHistoricalMap<p>Thanks to <span class="h-card" translate="no"><a href="https://mstdn.social/@bmacs001" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>bmacs001</span></a></span>, <a href="https://mapstodon.space/tags/OpenHistoricalMap" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenHistoricalMap</span></a> has comprehensive coverage of <a href="https://mapstodon.space/tags/NewJersey" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NewJersey</span></a> municipality boundaries over time. Watch the state get divvied up into counties, townships, boroughs, cities, towns, and villages in this mesmerizing <a href="https://mapstodon.space/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a>:</p><p><a href="https://www.reddit.com/r/newjersey/comments/1j4e1od/the_evolution_of_new_jerseys_county_and_municipal/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">reddit.com/r/newjersey/comment</span><span class="invisible">s/1j4e1od/the_evolution_of_new_jerseys_county_and_municipal/</span></a></p><p><a href="https://mapstodon.space/tags/Boroughitis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Boroughitis</span></a> <a href="https://mapstodon.space/tags/JerseyFresh" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>JerseyFresh</span></a></p>
Harald Klinke<p>A Look at TimeGPT with nixtlar in R<br>A first exploration of Nixtla’s TimeGPT, a Transformer-based model for time series forecasting, using the nixtlar R package. Learn how this self-attention architecture works and how to apply it in R.<br><a href="https://www.r-bloggers.com/2025/02/a-first-look-at-timegpt-using-nixtlar-2/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">r-bloggers.com/2025/02/a-first</span><span class="invisible">-look-at-timegpt-using-nixtlar-2/</span></a><br><a href="https://det.social/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a> <a href="https://det.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://det.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://det.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://det.social/tags/TimeGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeGPT</span></a></p>
Pierre-Simon Laplace<p>🔴 𝐇𝐨𝐰 𝐓𝐨 𝐅𝐨𝐜𝐮𝐬 𝐎𝐧 𝐖𝐡𝐚𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 𝐈𝐧 𝐓𝐢𝐦𝐞 𝐒𝐞𝐫𝐢𝐞𝐬 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠<br>🔗 <a href="https://learnbayesstats.com/episode/124-state-space-models-structural-time-series-jesse-grabowski" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">learnbayesstats.com/episode/12</span><span class="invisible">4-state-space-models-structural-time-series-jesse-grabowski</span></a></p><p>✅ 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐄𝐩𝐢𝐬𝐨𝐝𝐞, 𝐲𝐨𝐮’𝐥𝐥 𝐥𝐞𝐚𝐫𝐧 𝐡𝐨𝐰 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 with <span class="h-card" translate="no"><a href="https://bayes.club/@pymc" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>pymc</span></a></span> </p><p>Alex Andorra &amp; Jesse Grabowski talk about state space models, simplifying forecasting, applications etc.</p><p><a href="https://mstdn.science/tags/LearningBayesianStatistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LearningBayesianStatistics</span></a> <a href="https://mstdn.science/tags/PyMC" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PyMC</span></a> <a href="https://mstdn.science/tags/forecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forecasting</span></a> <a href="https://mstdn.science/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a></p>
Rami Krispin :unverified:<p>I am starting an email newsletter about time series analysis and forecasting. It is still WIP, but you can subscribe here:<br><a href="https://the-forecaster.beehiiv.com/subscribe" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">the-forecaster.beehiiv.com/sub</span><span class="invisible">scribe</span></a></p><p><a href="https://mstdn.social/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a> <a href="https://mstdn.social/tags/forecasting" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forecasting</span></a> <a href="https://mstdn.social/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a> <a href="https://mstdn.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://mstdn.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a></p>
bsull<p>The forecasting implementations are also heavily based on the OG Python and R versions, there's not a tremendous amount of new stuff there! Outlier and clustering are a bit more interesting at least.</p><p>Anyway, issues and PRs are welcome if you find something missing!</p><p><a href="https://grafana.social/tags/rustlang" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rustlang</span></a> <a href="https://grafana.social/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a></p>
Steven Sanderson<p>Can you tell when the new version of our <a href="https://rstats.me/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a> <a href="https://rstats.me/tags/package" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>package</span></a> <a href="https://rstats.me/tags/RandomWalker" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RandomWalker</span></a> was released?</p><p>I think you can :)</p><p><a href="https://rstats.me/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a> <a href="https://rstats.me/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://rstats.me/tags/RProgramming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RProgramming</span></a> <a href="https://rstats.me/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a> <a href="https://rstats.me/tags/Finance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Finance</span></a></p>
Estelle Platini<p>"The ‘science of finance’ is first and foremost a collective ethos. Its real achievement is not objective discovery but ethical articulation. […] It fixes the underlying terrain, it shows them the proper path to follow, and it compels them to stay on track. Without this anchor, all capitalists — whether they are small, anonymous day traders, legendary investors such as Warren Buffet, or professional fund managers like Bill Gross — would be utterly lost.</p><p>"Finance theory establishes the elementary particles of capitalization and the boundaries of accumulation. It gives capitalists the basic building blocks of investment; it tells them how to quantify these entities as numerical ‘variables’; and it provides them with a universal algorithm that reduces these variables into the single magnitude of present value."</p><p>(Nitzan and Bichler, 2009) 🧶</p><p><a href="https://techhub.social/tags/ownership" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ownership</span></a> <a href="https://techhub.social/tags/economics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>economics</span></a> <a href="https://techhub.social/tags/property" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>property</span></a> <a href="https://techhub.social/tags/valuation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>valuation</span></a> <a href="https://techhub.social/tags/capitalism" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>capitalism</span></a> <a href="https://techhub.social/tags/power" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>power</span></a> <a href="https://techhub.social/tags/finance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finance</span></a> <a href="https://techhub.social/tags/capital" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>capital</span></a> <a href="https://techhub.social/tags/actualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>actualization</span></a> <a href="https://techhub.social/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://techhub.social/tags/financialData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>financialData</span></a> <a href="https://techhub.social/tags/investing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>investing</span></a> <a href="https://techhub.social/tags/investment" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>investment</span></a></p>
Steven Sanderson<p>I have submitted a new <a href="https://rstats.me/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a> <a href="https://rstats.me/tags/package" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>package</span></a> yesterday with my co-author Antti Rask called RandomWalker</p><p>We are very excited about it!</p><p>GitHub: <a href="https://github.com/spsanderson/RandomWalker/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/spsanderson/RandomW</span><span class="invisible">alker/</span></a></p><p>WebSite: <a href="https://www.spsanderson.com/RandomWalker/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">spsanderson.com/RandomWalker/</span><span class="invisible"></span></a></p><p><a href="https://rstats.me/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a> <a href="https://rstats.me/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a> <a href="https://rstats.me/tags/RandomWalks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RandomWalks</span></a> <a href="https://rstats.me/tags/Stochastic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Stochastic</span></a> <a href="https://rstats.me/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a></p>
PLOS Biology<p>Testing <a href="https://fediscience.org/tags/significance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>significance</span></a> of a correlation between time series is a longstanding challenge. @ShouGroup presents the truncated time-shift (TTS) test, a significance test that is valid as long as one <a href="https://fediscience.org/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TimeSeries</span></a> is statistically stationary <a href="https://fediscience.org/tags/PLOSBiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PLOSBiology</span></a> <a href="https://plos.io/4dOvvGx" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">plos.io/4dOvvGx</span><span class="invisible"></span></a></p>
Steven P. Sanderson II, MPH<p>I have three logos for my new <a href="https://mstdn.social/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a> <a href="https://mstdn.social/tags/package" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>package</span></a> which do you think is better? Version 1, 2 or 3?</p><p>1 is the discrete version, </p><p>2 is the black squiggly line and </p><p>3 is the colored squiggly line.</p><p><a href="https://mstdn.social/tags/RandomWalks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RandomWalks</span></a> <a href="https://mstdn.social/tags/Random" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Random</span></a> <a href="https://mstdn.social/tags/timeseries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeseries</span></a> <a href="https://mstdn.social/tags/ggplot2" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ggplot2</span></a></p>
Eric Maugendre<p>"Extract Year from a datetime column", by Piyush Raj: <a href="https://datascienceparichay.com/article/pandas-extract-year-from-datetime-column/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">datascienceparichay.com/articl</span><span class="invisible">e/pandas-extract-year-from-datetime-column/</span></a></p><p><a href="https://hachyderm.io/tags/dataDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataDev</span></a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://hachyderm.io/tags/Pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Pandas</span></a> <a href="https://hachyderm.io/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://hachyderm.io/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/dataAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataAnalysis</span></a> <a href="https://hachyderm.io/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://hachyderm.io/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a></p>
Eric Maugendre<p>An easy guide to predict possible future quantities, by Mercy Kibet: <a href="https://www.influxdata.com/blog/guide-regression-analysis-time-series-data/#heading0" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">influxdata.com/blog/guide-regr</span><span class="invisible">ession-analysis-time-series-data/#heading0</span></a></p><p><a href="https://hachyderm.io/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://hachyderm.io/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/linearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linearRegression</span></a> <a href="https://hachyderm.io/tags/dataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataScience</span></a> <a href="https://hachyderm.io/tags/futures" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>futures</span></a> <a href="https://hachyderm.io/tags/money" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>money</span></a> <a href="https://hachyderm.io/tags/trends" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>trends</span></a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a></p>

(1/2) Introduction to Fourier Analysis 🚀

If you are looking to learn about the Fourier series and Fourier transformation, I highly recommend checking this short course by Prof. Steve Brunton from the University of Washington. Fourier series and Fourier transformation are widely used in many fields of science, such as time series forecasting, image and audio processing, etc.

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