<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Machine-Learning on AI Charcha</title><link>https://www.aicharcha.com/tags/machine-learning/</link><description>Recent content in Machine-Learning on AI Charcha</description><image><title>AI Charcha</title><url>https://www.aicharcha.com/images/aicharcha-logo-refresh-1.svg</url><link>https://www.aicharcha.com/images/aicharcha-logo-refresh-1.svg</link></image><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 21 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.aicharcha.com/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Feature Engineering for Machine Learning: A Practical Learning Guide</title><link>https://www.aicharcha.com/guides/feature-engineering-for-machine-learning/</link><pubDate>Sun, 21 Jun 2026 00:00:00 +0000</pubDate><guid>https://www.aicharcha.com/guides/feature-engineering-for-machine-learning/</guid><description>A beginner-friendly guide to feature engineering for machine learning, covering what features are, why they matter, common feature types, and a practical workflow.</description></item><item><title>Feature Engineering With Keras and BigQuery ML</title><link>https://www.aicharcha.com/guides/feature-engineering-with-keras-and-bigquery-ml/</link><pubDate>Sun, 21 Jun 2026 00:00:00 +0000</pubDate><guid>https://www.aicharcha.com/guides/feature-engineering-with-keras-and-bigquery-ml/</guid><description>A practical guide to feature engineering with Keras preprocessing layers and BigQuery ML, including normalization, encoding, bucketization, feature crosses, and TRANSFORM.</description></item><item><title>How to Choose Good Machine Learning Features</title><link>https://www.aicharcha.com/guides/how-to-choose-good-machine-learning-features/</link><pubDate>Sun, 21 Jun 2026 00:00:00 +0000</pubDate><guid>https://www.aicharcha.com/guides/how-to-choose-good-machine-learning-features/</guid><description>A practical checklist for choosing good machine learning features, avoiding leakage, checking prediction-time availability, and improving model quality.</description></item></channel></rss>