<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>deep learning on DataScience.LA</title><link>https://datasciencela.github.io/tag/deep-learning/</link><description>Recent content in deep learning on DataScience.LA</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>DataScience.LA, 2014–2021 · Read-only archive: comments are closed.</copyright><lastBuildDate>Thu, 13 Oct 2022 00:02:42 -0700</lastBuildDate><atom:link href="https://datasciencela.github.io/tag/deep-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>DSSTNE: A New Deep Learning Framework for Large Sparse Datasets</title><link>https://datasciencela.github.io/dsstne-a-new-deep-learning-framework-for-large-sparse-datasets/</link><pubDate>Fri, 14 Oct 2016 15:29:22 -0700</pubDate><guid>https://datasciencela.github.io/dsstne-a-new-deep-learning-framework-for-large-sparse-datasets/</guid><description>&lt;h3 class="relative group"&gt;&lt;strong&gt;Update: This event has ended. Slides are available &lt;a href="https://speakerdeck.com/datasciencela/scott-le-grand-dsstne-la-data-science-meetup-oct-2016"&gt;here&lt;/a&gt;.&lt;/strong&gt;&#10; &lt;div id="update-this-event-has-ended-slides-are-available" class="anchor"&gt;&lt;/div&gt;&#10; &#10; &lt;span&#10; class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"&gt;&#10; &lt;a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#update-this-event-has-ended-slides-are-available" aria-label="Anchor"&gt;#&lt;/a&gt;&#10; &lt;/span&gt;&#10; &#10;&lt;/h3&gt;&#10;&#10;&lt;h3 class="relative group"&gt;&lt;strong&gt;Update: Video recording by Carl Mullins:&lt;/strong&gt;&#10; &lt;div id="update-video-recording-by-carl-mullins" class="anchor"&gt;&lt;/div&gt;&#10; &#10; &lt;span&#10; class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"&gt;&#10; &lt;a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#update-video-recording-by-carl-mullins" aria-label="Anchor"&gt;#&lt;/a&gt;&#10; &lt;/span&gt;&#10; &#10;&lt;/h3&gt;&#10;&lt;p class="yt-unavailable"&gt;This video is no longer available on YouTube (&lt;a href="https://www.youtube.com/watch?v=AQ0EjOJnu9Q"&gt;original link&lt;/a&gt;).&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/dsstne-a-new-deep-learning-framework-for-large-sparse-datasets/feature.jpg"/></item><item><title>Deep Learning @Whisper</title><link>https://datasciencela.github.io/deep-learning-whisper/</link><pubDate>Tue, 03 May 2016 11:37:29 -0700</pubDate><guid>https://datasciencela.github.io/deep-learning-whisper/</guid><description>&lt;p&gt;&lt;strong&gt;Deep Learning @Whisper&lt;/strong&gt;&lt;br&gt;&#10;&lt;strong&gt;talk by Nick Stucky-Mack&lt;/strong&gt;&lt;/p&gt;&#10;&lt;p&gt;Video now available, thank you to community member Carl Mullins for providing video services:&lt;/p&gt;&#10;&lt;figure class="yt-lite" data-id="VDV8GzkftIc"&gt;&#10; &lt;a class="yt-lite-btn" href="https://www.youtube.com/watch?v=VDV8GzkftIc" title="Play: Deep Learning @Whisper THU, MAY 12 AT 6 00 PM, VENICE, CA"&gt;&#10; &lt;img src="https://i.ytimg.com/vi/VDV8GzkftIc/hqdefault.jpg" alt="Deep Learning @Whisper THU, MAY 12 AT 6 00 PM, VENICE, CA" loading="lazy" width="480" height="360"&gt;&#10; &lt;span class="yt-lite-play" aria-hidden="true"&gt;&lt;/span&gt;&#10; &lt;/a&gt;&#10; &lt;figcaption&gt;▶ Deep Learning @Whisper THU, MAY 12 AT 6 00 PM, VENICE, CA&lt;/figcaption&gt;&#10;&lt;/figure&gt;&#10;&lt;script&gt;&#10;document.addEventListener('click', function (e) {&#10; var a = e.target.closest('.yt-lite-btn'); if (!a) return;&#10; e.preventDefault();&#10; var f = a.parentNode, s = f.dataset.start, i = document.createElement('iframe');&#10; i.src = 'https://www.youtube-nocookie.com/embed/' + f.dataset.id + '?autoplay=1' + (s ? '&amp;start=' + s : '');&#10; i.title = a.title; i.allowFullscreen = true;&#10; i.allow = 'accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture';&#10; a.replaceWith(i);&#10;});&#10;&lt;/script&gt;&#10;&lt;p&gt;In this talk we will discuss how Whisper uses machine learning for natural  language processing tasks. We will focus on how Whisper applies deep learning to moderate content created by its more than 20 million monthly active users. The talk will explore the problem of short text classification, and will cover Whisper&amp;rsquo;s choices in machine learning models, software development, and hardware.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/deep-learning-whisper/feature.png"/></item><item><title>PyDSLA Video: Carlos Guestrin, CEO of DATO</title><link>https://datasciencela.github.io/pydsla-video-carlos-guestrin-ceo-of-dato/</link><pubDate>Thu, 18 Jun 2015 15:53:26 -0700</pubDate><guid>https://datasciencela.github.io/pydsla-video-carlos-guestrin-ceo-of-dato/</guid><description>&lt;p&gt;On May 14th at the Venice Arts Center, the Los Angeles Python and Data Science communities were fortunate to hear a talk from world-renowned expert and CEO of Dato, Carlos Guestrin. Often times when you have a meetup where a presenter is tightly identified with a company, the concern is that the presentation will fundamentally become a product pitch. We had nothing to be worried about in this case - Carlos presented for nearly an hour on a wide range of subjects from how the Machine Learning pipeline has changed over time to Deep Learning!&lt;/p&gt;</description></item></channel></rss>