<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/ill-be-talking-about-decoding-the-black-box-at-the-frankfurt-data-science-meetup/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="https://shirinsplayground.netlify.com/2018/09/ffm_datascience_meetup/"> Shirin's playgRound</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>I have yet another Meetup talk to announce:</p>
<p>On Wednesday, October 26th, I’ll be talking about <a rel="nofollow" href="http://meetu.ps/e/DQBZx/w54bW/f" target="_blank">‘Decoding The Black Box’ at the Frankfurt Data Science Meetup</a>.</p>
<p>Particularly cool with this meetup is that they will livestream the event at <a rel="nofollow" href="https://shirinsplayground.netlify.com/2018/09/ffm_datascience_meetup/www.youtube.com/c/FrankfurtDataScience" target="_blank">www.youtube.com/c/FrankfurtDataScience</a>!</p>
<blockquote>
<p>TALK#2: DECODING THE BLACK BOX</p>
</blockquote>
<blockquote>
<p>And finally we will have with us Dr.Shirin Glander, whom we were inviting for a long time back. Shirin lives in Münster and works as a Data Scientist at codecentric, she has lots of practical experience. Besides crunching data, she trains her creativity by sketching information. Visit her blog and you will find lots of interesting stuff there, like experimenting with Keras, TensorFlow, LIME, caret, lots of R and also her beautiful sketches. We recommend: www.shirin-glander.de Besides all that she is an organiser of MünsteR – R User Group: www.meetup.com/Munster-R-Users-Group</p>
</blockquote>
<blockquote>
<p>Traditional ML workflows focus heavily on model training and optimization; the best model is usually chosen via performance measures like accuracy or error and we tend to assume that a model is good enough for deployment if it passes certain thresholds of these performance criteria. Why a model makes the predictions it makes, however, is generally neglected. But being able to understand and interpret such models can be immensely important for improving model quality, increasing trust and transparency and for reducing bias. Because complex ML models are essentially black boxes and too complicated to understand, we need to use approximations, like LIME.</p>
</blockquote>
	<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://shirinsplayground.netlify.com/2018/09/ffm_datascience_meetup/"> Shirin's playgRound</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a rel="nofollow" href="https://www.r-project.org/" title="The R Project for Statistical Computing">R</a> news and <a rel="nofollow" href="https://www.r-bloggers.com/search/tutorial" title="R tutorials">tutorials</a> on topics such as: <a rel="nofollow" href="https://www.r-bloggers.com/search/data%20science" title="Data science">Data science</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data" title="Big Data">Big Data, <a rel="nofollow" href="https://www.r-users.com/" title="R jobs">R jobs</a>, visualization (<a rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2" title="ggplot and ggplot2 tutorials">ggplot2</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/boxplot" title="Boxplots using lattice and ggplot2 tutorials">Boxplots</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/map" title="Maps and gis">maps</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/animation" title="Animation in R">animation</a>), programming (<a rel="nofollow" href="https://www.r-bloggers.com/search/RStudio" title="RStudio IDE for R">RStudio</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/sweave" title="Sweave and literate programming">Sweave</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX" title="LaTeX in R">LaTeX</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/SQL" title="SQL and databases">SQL</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/eclipse" title="Eclipse IDE for R">Eclipse</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/git" title="git and github, Version Control System">git</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/hadoop" title="Large data in R using Hadoop">hadoop</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping" title="Web Scraping of google, facebook, yahoo, twitter and more using R">Web Scraping</a>) statistics (<a rel="nofollow" href="https://www.r-bloggers.com/search/regression" title="Regressions and ANOVA analysis tutorials">regression</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/PCA" title="principal component analysis tutorial">PCA</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/time+series" title="Time series">time series</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/trading" title="finance trading">trading</a>) and more...
<img width="1" alt="" src="http://feeds.feedburner.com/~r/RBloggers/~4/K4ZebyVCYr0" height="1"></a></div>