<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning, X-AI | Maaz Salman</title><link>https://maazsalman.com/tags/machine-learning-x-ai/</link><atom:link href="https://maazsalman.com/tags/machine-learning-x-ai/index.xml" rel="self" type="application/rss+xml"/><description>Machine Learning, X-AI</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 01 Jan 2023 00:00:00 +0000</lastBuildDate><image><url>https://maazsalman.com/media/icon_hub75224e924a801dac222e2220d610f2c_32468_512x512_fill_lanczos_center_3.png</url><title>Machine Learning, X-AI</title><link>https://maazsalman.com/tags/machine-learning-x-ai/</link></image><item><title>Explainable AI (XAI) Hybrid CNN-LSTM with Attention</title><link>https://maazsalman.com/project/explainable-ai-xai-hybridcnnlstmwithattention/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://maazsalman.com/project/explainable-ai-xai-hybridcnnlstmwithattention/</guid><description>&lt;h2 id="-project-overview">🔬 Project Overview&lt;/h2>
&lt;p>The primary purpose of this script is to build, train, evaluate, and explain a hybrid deep learning model for a classification task. The model combines Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), and an Attention mechanism.&lt;/p>
&lt;h2 id="-technical-details">⚙️ Technical Details&lt;/h2>
&lt;ul>
&lt;li>SHAP (SHapley Additive exPlanations) Analysis&lt;/li>
&lt;li>Grad-CAM (Gradient-weighted Class Activation Mapping)&lt;/li>
&lt;li>Attention Weights Visualization&lt;/li>
&lt;/ul>
&lt;p>&lt;em>(For full source code, pin configurations, and implementation details, please view the GitHub repository using the button above).&lt;/em>&lt;/p></description></item></channel></rss>