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<description>henrik&#39;s bookmarks in folder Machine Learning on Netvouz</description>
<item><title>Data Science tutorial</title>
<link>https://youtube.com/playlist?list=PLKYEe2WisBTECZ8mZCfFxzrBBuGrS1Gfu</link>
<description>Numpy, pandas, scikit, linear and logistic regression, Movies to walk you through basic concepts</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Sun, 20 Mar 2022 08:36:40 GMT</pubDate>
</item><item><title>GitHub - HeroKillerEver/coursera-deep-learning</title>
<link>https://github.com/HeroKillerEver/coursera-deep-learning</link>
<description>Solutions to all quiz and all the programming assignments!!!</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Wed, 02 Jan 2019 17:55:03 GMT</pubDate>
</item><item><title>GitHub - Kulbear/deep-learning-coursera</title>
<link>https://github.com/Kulbear/deep-learning-coursera</link>
<description>Deep Learning Specialization by Andrew Ng on Coursera.</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Wed, 12 Sep 2018 10:38:21 GMT</pubDate>
</item><item><title>Google Dataset Search</title>
<link>https://datasetsearch.research.google.com/</link>
<description>Search for public data sources for your data analytics or data science project;</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Mon, 27 Jan 2020 14:19:27 GMT</pubDate>
</item><item><title>kPOD This Python package implements an extension to the k-means clustering algorithm for use with missing data.</title>
<link>https://github.com/iiradia/kPOD</link>
<description>The k-POD method presents a simple extension of k-means clustering for missing data that works even when the missingness mechanism is unknown, when external information is unavailable, and when there is significant missingness in the data. In addition, k-POD presents strong advantages in computation time and resources over other methods for removing missingness, while still maintaining accuracy.</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Thu, 10 Mar 2022 09:37:04 GMT</pubDate>
</item><item><title>Node.js meets OpenCV’s Deep Neural Networks — Fun with Tensorflow and Caffe</title>
<link>https://medium.com/@muehler.v/node-js-meets-opencvs-deep-neural-networks-fun-with-tensorflow-and-caffe-ff8d52a0f072</link>
<description>In this tutorial we are going to learn how to load pretrained models from Tensorflow and Caffe with OpenCV’s DNN module and we will dive into two examples for object recognition with Node.js and OpenCV.</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Fri, 27 Apr 2018 05:47:12 GMT</pubDate>
</item><item><title>OpenCV 4 Node.js</title>
<link>https://github.com/justadudewhohacks/opencv4nodejs</link>
<description>Asynchronous OpenCV 3.x nodejs bindings with JavaScript and TypeScript API, with examples for: Face Detection, Machine Learning, Deep Neural Nets, Hand Gesture Recognition, Object Tracking, Feature Matching, Image Histogram</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Fri, 27 Apr 2018 05:44:20 GMT</pubDate>
</item><item><title>Stanford Machine Learning | Coursera</title>
<link>https://www.coursera.org/learn/machine-learning/home/welcome</link>
<description>Machine Learning course from Stanford University @ coursera</description>
<category domain="http://netvouz.com/henrik?category=3788618044265731538">Development &gt; Machine Learning</category>
<author>henrik</author>
<pubDate>Mon, 20 Feb 2017 14:00:26 GMT</pubDate>
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