<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>http://direct.ecency.com</link><image><url>http://direct.ecency.com/logo512.png</url><title>RSS Feed</title><link>http://direct.ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Wed, 08 Apr 2026 06:48:10 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/@cryptoone/rss" rel="self" type="application/rss+xml"/><item><title><![CDATA[How to solve 90% of NLP problems: a step-by-step guide]]></title><link>http://direct.ecency.com/nlp/@cryptoone/how-to-solve-90-of-nlp-problems-a-step-by-step-guide</link><guid isPermaLink="true">http://direct.ecency.com/nlp/@cryptoone/how-to-solve-90-of-nlp-problems-a-step-by-step-guide</guid><category><![CDATA[nlp]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Tue, 06 Mar 2018 15:46:57 GMT</pubDate></item><item><title><![CDATA[Understanding the mAP Evaluation Metric for Object Detection]]></title><link>http://direct.ecency.com/map/@cryptoone/understanding-the-map-evaluation-metric-for-object-detection</link><guid isPermaLink="true">http://direct.ecency.com/map/@cryptoone/understanding-the-map-evaluation-metric-for-object-detection</guid><category><![CDATA[map]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Tue, 06 Mar 2018 15:35:54 GMT</pubDate></item><item><title><![CDATA[Only Numpy: Deriving Forward feed and Back Propagation in Long Short Term Memory (LSTM) part 1]]></title><link>http://direct.ecency.com/numpy/@cryptoone/only-numpy-deriving-forward-feed-and-back-propagation-in-long-short-term-memory-lstm-part-1</link><guid isPermaLink="true">http://direct.ecency.com/numpy/@cryptoone/only-numpy-deriving-forward-feed-and-back-propagation-in-long-short-term-memory-lstm-part-1</guid><category><![CDATA[numpy]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Sat, 03 Mar 2018 18:25:39 GMT</pubDate></item><item><title><![CDATA[Only Numpy: Vanilla Recurrent Neural Network Deriving Back propagation Through Time Practice — part 1/2]]></title><link>http://direct.ecency.com/numpy/@cryptoone/only-numpy-vanilla-recurrent-neural-network-deriving-back-propagation-through-time-practice-part-1-2</link><guid isPermaLink="true">http://direct.ecency.com/numpy/@cryptoone/only-numpy-vanilla-recurrent-neural-network-deriving-back-propagation-through-time-practice-part-1-2</guid><category><![CDATA[numpy]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Sat, 03 Mar 2018 18:19:57 GMT</pubDate></item><item><title><![CDATA[Interpretable Machine Learning through Teaching]]></title><link>http://direct.ecency.com/openai/@cryptoone/interpretable-machine-learning-through-teaching</link><guid isPermaLink="true">http://direct.ecency.com/openai/@cryptoone/interpretable-machine-learning-through-teaching</guid><category><![CDATA[openai]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Thu, 01 Mar 2018 16:00:24 GMT</pubDate></item><item><title><![CDATA[Building Prediction APIs in Python (Part 1): Series Introduction & Basic Example]]></title><description><![CDATA[Building Prediction APIs in Python (Part 1): Series Introduction & Basic Example Ok, so you’ve trained a model, but now what? All that work is meaningless if no one can use it. In some applications,]]></description><link>http://direct.ecency.com/python/@cryptoone/building-prediction-apis-in-python-part-1-series-introduction-and-basic-example</link><guid isPermaLink="true">http://direct.ecency.com/python/@cryptoone/building-prediction-apis-in-python-part-1-series-introduction-and-basic-example</guid><category><![CDATA[python]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Thu, 22 Feb 2018 17:25:03 GMT</pubDate><enclosure url="https://images.ecency.com/p/2N61tyyncFaFnNFKLegVvzmsrMAExSDXzsHdqwaiSkbtRMy5Vt84bt67fL3TaEP9zkiXVETNS1sZ1bCPFGkcKiUWAbdQHDZCzbQwcidkM8a7KrjCfwPGhym5ccjbeSk1VbYWRPGE5BHG?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Only Numpy: Implementing Mini VGG (VGG 7) and SoftMax Layer with Interactive Code]]></title><link>http://direct.ecency.com/numpy/@cryptoone/only-numpy-implementing-mini-vgg-vgg-7-and-softmax-layer-with-interactive-code</link><guid isPermaLink="true">http://direct.ecency.com/numpy/@cryptoone/only-numpy-implementing-mini-vgg-vgg-7-and-softmax-layer-with-interactive-code</guid><category><![CDATA[numpy]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Wed, 21 Feb 2018 17:50:24 GMT</pubDate></item><item><title><![CDATA[Real time object detection using tensorflow]]></title><description><![CDATA[Real-time Object Detection on Android using Tensorflow Overview Research shows that the detection of objects like a human eye has not been achieved with high accuracy using cameras and cameras cannot be]]></description><link>http://direct.ecency.com/tensorflow/@cryptoone/real-time-object-detection-using-tensorflow</link><guid isPermaLink="true">http://direct.ecency.com/tensorflow/@cryptoone/real-time-object-detection-using-tensorflow</guid><category><![CDATA[tensorflow]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Wed, 21 Feb 2018 17:45:03 GMT</pubDate></item></channel></rss>